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A

AbstractContext - Class in net.librec.common
Abstract Context
AbstractContext() - Constructor for class net.librec.common.AbstractContext
 
AbstractDataConvertor - Class in net.librec.data.convertor
A AbstractDataConvertor is a class to convert a data file from one source format to a target format.
AbstractDataConvertor() - Constructor for class net.librec.data.convertor.AbstractDataConvertor
 
AbstractDataModel - Class in net.librec.data.model
A AbstractDataModel represents a data access class to the input file.
AbstractDataModel() - Constructor for class net.librec.data.model.AbstractDataModel
 
AbstractDataSplitter - Class in net.librec.data.splitter
Abstract Data Splitter
AbstractDataSplitter() - Constructor for class net.librec.data.splitter.AbstractDataSplitter
 
AbstractRecommender - Class in net.librec.recommender
Abstract Recommender Methods
AbstractRecommender() - Constructor for class net.librec.recommender.AbstractRecommender
 
AbstractRecommenderEvaluator - Class in net.librec.eval
Abstract Recommender Evaluator
AbstractRecommenderEvaluator() - Constructor for class net.librec.eval.AbstractRecommenderEvaluator
 
AbstractRecommenderSimilarity - Class in net.librec.similarity
Calculate Recommender Similarity, such as cosine, Pearson, Jaccard similarity, etc.
AbstractRecommenderSimilarity() - Constructor for class net.librec.similarity.AbstractRecommenderSimilarity
 
add(int, int, double) - Method in class net.librec.math.structure.DenseMatrix
Add a value to entry [row, column]
add(DenseMatrix) - Method in class net.librec.math.structure.DenseMatrix
Do A + B matrix operation
add(SparseMatrix) - Method in class net.librec.math.structure.DenseMatrix
Do A + B matrix operation
add(double) - Method in class net.librec.math.structure.DenseMatrix
Do A + c matrix operation, where c is a constant.
add(int, double) - Method in class net.librec.math.structure.DenseVector
Add a value to entry [index]
add(double) - Method in class net.librec.math.structure.DenseVector
Return a new dense vector by adding a value to all entries of current vector a[i] = b[i] + c
add(DenseVector) - Method in class net.librec.math.structure.DenseVector
Do vector operation: a + b
add(DiagMatrix) - Method in class net.librec.math.structure.DiagMatrix
do B + C diagonal matrix operation
add(double) - Method in class net.librec.math.structure.DiagMatrix
Each diagonal entry addes val
add(int, int, double) - Method in class net.librec.math.structure.SparseMatrix
Add a value to entry [row, column]
add(int, int, double) - Method in class net.librec.math.structure.SparseStringMatrix
Add a value to entry [row, column]
add(double, int...) - Method in class net.librec.math.structure.SparseTensor
Add a value to a given i-entry
add(int, double) - Method in class net.librec.math.structure.SparseVector
Add a value to entry [idx]
add(int, int, double) - Method in class net.librec.math.structure.SymmMatrix
add a value to entry (row, col)
addDefaultResource(String) - Static method in class net.librec.conf.Configuration
Add a default resource.
addEqual(DenseMatrix) - Method in class net.librec.math.structure.DenseMatrix
Do A + B matrix operation
addEqual(SparseMatrix) - Method in class net.librec.math.structure.DenseMatrix
Do A + B matrix operation
addEqual(double) - Method in class net.librec.math.structure.DenseMatrix
Do A + c matrix operation, where c is a constant.
addEqual(double) - Method in class net.librec.math.structure.DenseVector
Return this dense vector by adding a value to all entries of current vector b[i] = b[i] + c
addEqual(DenseVector) - Method in class net.librec.math.structure.DenseVector
Do vector operation: a + b
addEqual(DiagMatrix) - Method in class net.librec.math.structure.DiagMatrix
do B + C diagonal matrix operation
addEqual(double) - Method in class net.librec.math.structure.DiagMatrix
Each diagonal entry addes val
addItemIdxList(int, ArrayList<ItemEntry<Integer, Double>>) - Method in class net.librec.recommender.item.RecommendedItemList
append the specified element to the end of this list.
addResource(Configuration.Resource) - Method in class net.librec.conf.Configuration
 
addSimilarities(String, RecommenderSimilarity) - Method in class net.librec.recommender.RecommenderContext
 
addUserItemIdx(int, int, double) - Method in class net.librec.recommender.item.RecommendedItemList
Appends the specified element to the end of this list.
addUserItemIdx(int, int, double) - Method in interface net.librec.recommender.item.RecommendedList
add UserItemIdx
alpha - Variable in class net.librec.recommender.cf.ranking.ItemBigramRecommender
vector of hyperparameters for alpha
alpha - Variable in class net.librec.recommender.cf.ranking.LDARecommender
vector of hyperparameters for alpha and beta
AoBPRRecommender - Class in net.librec.recommender.cf.ranking
AoBPR: BPR with Adaptive Oversampling
AoBPRRecommender() - Constructor for class net.librec.recommender.cf.ranking.AoBPRRecommender
 
append(int, double) - Method in class net.librec.math.structure.SparseVector
append a value to entry [idx] if the idx is sorted
ArffAttribute - Class in net.librec.data.model
A ArffAttribute is a class to represent attribute of ARFF format input.
ArffAttribute(String, String, int) - Constructor for class net.librec.data.model.ArffAttribute
Initializes a newly created ArffAttribute object with the name type and index of a attribute.
ArffDataConvertor - Class in net.librec.data.convertor
A ArffDataConvertor is a class to convert a data file from ARFF format to a target format.
ArffDataConvertor(String) - Constructor for class net.librec.data.convertor.ArffDataConvertor
Initializes a newly created ArffDataConvertor object with the path of the input data file.
ArffDataConvertor(String, ArrayList<BiMap<String, Integer>>) - Constructor for class net.librec.data.convertor.ArffDataConvertor
 
ArffDataModel - Class in net.librec.data.model
A ArffDataModel represents a data access class to the ARFF format input.
ArffDataModel() - Constructor for class net.librec.data.model.ArffDataModel
Empty constructor.
ArffDataModel(Configuration) - Constructor for class net.librec.data.model.ArffDataModel
Initializes a newly created ArffDataModel object with configuration.
ArffInstance - Class in net.librec.data.model
A ArffInstance represents an instance of ARFF format input.
ArffInstance(ArrayList<String>) - Constructor for class net.librec.data.model.ArffInstance
Initializes a newly created ArffInstance object with instance data.
ArffSVMPreference - Class in net.librec.data.preference
Deprecated.
ArffSVMPreference() - Constructor for class net.librec.data.preference.ArffSVMPreference
Deprecated.
 
arrayToString(String[]) - Static method in class net.librec.util.StringUtil
Given an array of strings, return a comma-separated list of its elements.
arrayToString(int[]) - Static method in class net.librec.util.StringUtil
Given an array of int, return a comma-separated list of its elements.
AspectModelRecommender - Class in net.librec.recommender.cf.ranking
Latent class models for collaborative filtering
AspectModelRecommender() - Constructor for class net.librec.recommender.cf.ranking.AspectModelRecommender
 
AspectModelRecommender - Class in net.librec.recommender.cf.rating
Latent class models for collaborative filtering
AspectModelRecommender() - Constructor for class net.librec.recommender.cf.rating.AspectModelRecommender
 
AssociationRuleRecommender - Class in net.librec.recommender.ext
Choonho Kim and Juntae Kim, A Recommendation Algorithm Using Multi-Level Association Rules, WI 2003.
AssociationRuleRecommender() - Constructor for class net.librec.recommender.ext.AssociationRuleRecommender
 
ASVDPlusPlusRecommender - Class in net.librec.recommender.cf.rating
Yehuda Koren, Factorization Meets the Neighborhood: a Multifaceted Collaborative Filtering Model., KDD 2008.
ASVDPlusPlusRecommender() - Constructor for class net.librec.recommender.cf.rating.ASVDPlusPlusRecommender
 
attrs - Static variable in class net.librec.data.model.ArffInstance
Attributes of the instance
AUCEvaluator - Class in net.librec.eval.ranking
AUCEvaluator
AUCEvaluator() - Constructor for class net.librec.eval.ranking.AUCEvaluator
 
autoCompress - Variable in class net.librec.math.structure.SparseVector
 
average(List<Double>, List<Double>) - Static method in class net.librec.math.algorithm.Stats
Return weighted average value of data and weights.
AveragePrecisionEvaluator - Class in net.librec.eval.ranking
AveragePrecisionEvaluator, calculate the MAP@n
AveragePrecisionEvaluator() - Constructor for class net.librec.eval.ranking.AveragePrecisionEvaluator
 
AverageReciprocalHitRankEvaluator - Class in net.librec.eval.ranking
HitRateEvaluator
AverageReciprocalHitRankEvaluator() - Constructor for class net.librec.eval.ranking.AverageReciprocalHitRankEvaluator
 

B

b - Variable in class net.librec.recommender.cf.rating.GPLSARecommender
 
bernoulli(double) - Static method in class net.librec.math.algorithm.Randoms
Return a boolean, which is true with probability p, and false otherwise.
bernoulli() - Static method in class net.librec.math.algorithm.Randoms
Return a boolean, which is true with probability .5, and false otherwise.
beta - Variable in class net.librec.recommender.cf.ranking.LDARecommender
vector of hyperparameters for alpha and beta
BHFreeRecommender - Class in net.librec.recommender.cf
Barbieri et al., Balancing Prediction and Recommendation Accuracy: Hierarchical Latent Factors for Preference Data, SDM 2012.
BHFreeRecommender() - Constructor for class net.librec.recommender.cf.BHFreeRecommender
 
BiasedMFRecommender - Class in net.librec.recommender.cf.rating
Biased Matrix Factorization Recommender
BiasedMFRecommender() - Constructor for class net.librec.recommender.cf.rating.BiasedMFRecommender
 
BinaryCosineSimilarity - Class in net.librec.similarity
Binary cosine similarity
BinaryCosineSimilarity() - Constructor for class net.librec.similarity.BinaryCosineSimilarity
 
BPMFRecommender - Class in net.librec.recommender.cf.rating
Salakhutdinov and Mnih, Bayesian Probabilistic Matrix Factorization using Markov Chain Monte Carlo, ICML 2008.
BPMFRecommender() - Constructor for class net.librec.recommender.cf.rating.BPMFRecommender
 
BPMFRecommender.HyperParameters - Class in net.librec.recommender.cf.rating
 
BPoissMFRecommender - Class in net.librec.recommender.cf.rating
Prem Gopalan, et al.
BPoissMFRecommender() - Constructor for class net.librec.recommender.cf.rating.BPoissMFRecommender
 
BPoissMFRecommender.GammaDenseMatrix - Class in net.librec.recommender.cf.rating
 
BPoissMFRecommender.GammaDenseMatrixGR - Class in net.librec.recommender.cf.rating
 
BPoissMFRecommender.GammaDenseVector - Class in net.librec.recommender.cf.rating
 
BPRRecommender - Class in net.librec.recommender.cf.ranking
Rendle et al., BPR: Bayesian Personalized Ranking from Implicit Feedback, UAI 2009.
BPRRecommender() - Constructor for class net.librec.recommender.cf.ranking.BPRRecommender
 
BUCMRecommender - Class in net.librec.recommender.cf
Bayesian UCM: Nicola Barbieri et al., Modeling Item Selection and Relevance for Accurate Recommendations: a Bayesian Approach, RecSys 2011.
BUCMRecommender() - Constructor for class net.librec.recommender.cf.BUCMRecommender
 
buildConvert() - Method in class net.librec.data.model.AbstractDataModel
Build Convert.
buildConvert() - Method in class net.librec.data.model.ArffDataModel
Build model.
buildConvert() - Method in class net.librec.data.model.JDBCDataModel
 
buildConvert() - Method in class net.librec.data.model.TextDataModel
Build Convert.
buildDataModel() - Method in interface net.librec.data.DataModel
Build data model.
buildDataModel() - Method in class net.librec.data.model.AbstractDataModel
Build data model.
buildFeature() - Method in class net.librec.data.model.AbstractDataModel
Build appender data.
buildIndex(int...) - Method in class net.librec.math.structure.SparseTensor
build index at dimensions nd
buildIndices() - Method in class net.librec.math.structure.SparseTensor
build index for all dimensions
buildSimilarityMatrix(DataModel) - Method in class net.librec.similarity.AbstractRecommenderSimilarity
Build social similarity matrix with trainMatrix in dataModel.
buildSimilarityMatrix(DataModel) - Method in class net.librec.similarity.CPCSimilarity
Build social similarity matrix with trainMatrix in dataModel.
buildSimilarityMatrix(DataModel) - Method in interface net.librec.similarity.RecommenderSimilarity
build and compute similarity matrix by dataModel
buildSocialSimilarityMatrix(DataModel) - Method in class net.librec.similarity.AbstractRecommenderSimilarity
Build social similarity matrix with trainMatrix and socialMatrix in dataModel.
buildSplitter() - Method in class net.librec.data.model.AbstractDataModel
Build Splitter.
buildSplitter() - Method in class net.librec.data.model.ArffDataModel
Build Splitter.
burnIn - Variable in class net.librec.recommender.ProbabilisticGraphicalRecommender
burn-in period

C

cacheSpec - Static variable in class net.librec.recommender.cf.ranking.FISMaucRecommender
Guava cache configuration
cacheSpec - Static variable in class net.librec.recommender.cf.ranking.FISMrmseRecommender
Guava cache configuration
cacheSpec - Static variable in class net.librec.recommender.cf.ranking.GBPRRecommender
Guava cache configuration
cacheSpec - Static variable in class net.librec.recommender.cf.ranking.WBPRRecommender
Guava cache configuration
cacheSpec - Static variable in class net.librec.recommender.context.ranking.SBPRRecommender
Guava cache configuration
cacheSpec - Static variable in class net.librec.recommender.context.rating.TimeSVDRecommender
Guava cache configuration
cacheSpec - Static variable in class net.librec.recommender.context.rating.TrustSVDRecommender
Guava cache configuration
cacheSpec - Static variable in class net.librec.recommender.ext.AssociationRuleRecommender
Guava cache configuration
capacity - Variable in class net.librec.math.structure.SparseVector
 
captureScreen() - Static method in class net.librec.util.Systems
Capture screen the with the name screenshot.png
captureScreen(String) - Static method in class net.librec.util.Systems
Capture screen with the input string as file name
cauchy() - Static method in class net.librec.math.algorithm.Randoms
Return a real number with a Cauchy distribution.
cdf(double) - Static method in class net.librec.math.algorithm.Gaussian
standard Gaussian cdf using Taylor approximation;
cdf(double, double, double) - Static method in class net.librec.math.algorithm.Gaussian
Gaussian cdf with mean mu and stddev sigma
check(int) - Method in class net.librec.math.structure.SparseVector
Checks the index
cholesky() - Method in class net.librec.math.structure.DenseMatrix
 
cleanDirectory(String) - Static method in class net.librec.util.FileUtil
 
cleanDirectory(File) - Static method in class net.librec.util.FileUtil
 
cleanup() - Method in class net.librec.recommender.AbstractRecommender
cleanup
cleanup() - Method in class net.librec.recommender.TensorRecommender
cleanup
clear() - Method in class net.librec.math.structure.DenseMatrix
Clear and reset all entries to 0.
clearCache() - Static method in class net.librec.math.algorithm.Randoms
 
CLIMFRecommender - Class in net.librec.recommender.cf.ranking
Shi et al., Climf: learning to maximize reciprocal rank with collaborative less-is-more filtering., RecSys 2012.
CLIMFRecommender() - Constructor for class net.librec.recommender.cf.ranking.CLIMFRecommender
 
clone() - Method in class net.librec.math.structure.DenseMatrix
Make a deep copy of current matrix
clone() - Method in class net.librec.math.structure.DenseVector
Make a deep copy of current vector
clone() - Method in class net.librec.math.structure.DiagMatrix
 
clone() - Method in class net.librec.math.structure.SparseMatrix
Make a deep clone of current matrix
clone() - Method in class net.librec.math.structure.SparseStringMatrix
Make a deep clone of current matrix
clone() - Method in class net.librec.math.structure.SparseTensor
make a deep clone
clone() - Method in class net.librec.math.structure.SymmMatrix
Make a deep copy of current matrix
closeQuietly(Reader) - Static method in class net.librec.util.IOUtil
Unconditionally close an Reader.
closeQuietly(Writer) - Static method in class net.librec.util.IOUtil
Unconditionally close a Writer.
closeQuietly(InputStream) - Static method in class net.librec.util.IOUtil
Unconditionally close an InputStream.
closeQuietly(OutputStream) - Static method in class net.librec.util.IOUtil
Unconditionally close an OutputStream.
colData - Variable in class net.librec.math.structure.SparseMatrix
 
colData - Variable in class net.librec.math.structure.SparseStringMatrix
 
colInd - Variable in class net.librec.math.structure.SparseMatrix
 
colInd - Variable in class net.librec.math.structure.SparseStringMatrix
 
colIterator(int) - Method in class net.librec.math.structure.SparseMatrix
 
colMap - Variable in class net.librec.math.structure.SparseStringMatrix
 
colMult(DenseMatrix, int, DenseMatrix, int) - Static method in class net.librec.math.structure.DenseMatrix
Inner product of two column vectors
colPtr - Variable in class net.librec.math.structure.SparseMatrix
 
colPtr - Variable in class net.librec.math.structure.SparseStringMatrix
 
column(int) - Method in class net.librec.math.structure.DenseMatrix
Return a copy of column data as a dense vector.
column() - Method in interface net.librec.math.structure.MatrixEntry
Returns the current column index
column(int) - Method in class net.librec.math.structure.SparseMatrix
get a col sparse vector of a matrix
columnCache(String) - Method in class net.librec.math.structure.SparseMatrix
create a column cache of a matrix
columnMean(int) - Method in class net.librec.math.structure.DenseMatrix
Compute mean of a column of the current matrix.
columnRowsCache(String) - Method in class net.librec.math.structure.SparseMatrix
create a row cache of a matrix in {row, row-specific columns}
columnRowsCache(String) - Method in class net.librec.math.structure.SparseStringMatrix
create a row cache of a matrix in {row, row-specific columns}
columns() - Method in class net.librec.math.structure.SparseMatrix
 
columns() - Method in class net.librec.math.structure.SparseStringMatrix
 
columnSize(int) - Method in class net.librec.math.structure.SparseMatrix
query the size of a specific col
columnSize(int) - Method in class net.librec.math.structure.SparseStringMatrix
query the size of a specific col
comma - Static variable in class net.librec.util.FileUtil
 
compareTo(RatingContext) - Method in class net.librec.util.RatingContext
 
compress() - Method in class net.librec.math.structure.SparseVector
compress the sparse vector
computeExpectations() - Method in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrix
 
computeExpectations() - Method in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrixGR
 
computeExpectations() - Method in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseVector
 
cond() - Method in class net.librec.math.algorithm.SVD
Two norm condition number
conf - Variable in class net.librec.common.AbstractContext
 
conf - Variable in class net.librec.conf.Configured
 
conf - Variable in class net.librec.eval.AbstractRecommenderEvaluator
configuration of the evaluator
conf - Variable in class net.librec.recommender.AbstractRecommender
conf
conf - Variable in class net.librec.recommender.TensorRecommender
conf
conf - Variable in class net.librec.similarity.AbstractRecommenderSimilarity
Configuration
CONF_DATA_COLUMN_FORMAT - Static variable in class net.librec.conf.Configured
 
CONF_DATA_INPUT_PATH - Static variable in class net.librec.conf.Configured
 
CONF_DFS_DATA_DIR - Static variable in class net.librec.conf.Configured
 
Configurable - Interface in net.librec.conf
Something that may be configured with a Configuration.
Configuration - Class in net.librec.conf
Provides access to configuration parameters.
Configuration() - Constructor for class net.librec.conf.Configuration
 
Configuration.Resource - Class in net.librec.conf
 
Configured - Class in net.librec.conf
Base class for things that may be configured with a Configuration.
Configured() - Constructor for class net.librec.conf.Configured
Construct a Configured.
Configured(Configuration) - Constructor for class net.librec.conf.Configured
Construct a Configured.
confindenceMinusIdentityMatrix - Variable in class net.librec.recommender.cf.ranking.WRMFRecommender
confindence Minus Identity Matrix{ui} = confidenceMatrix_{ui} - 1 =alpha * r_{ui} or log(1+10^alpha * r_{ui})
ConstantGuessRecommender - Class in net.librec.recommender.baseline
Baseline: predict by a constant rating
ConstantGuessRecommender() - Constructor for class net.librec.recommender.baseline.ConstantGuessRecommender
 
contains(int, int) - Method in class net.librec.math.structure.SparseMatrix
Retrieve value at entry [row, column]
contains(int...) - Method in class net.librec.math.structure.SparseTensor
Check if a given keys exists
contains(int) - Method in class net.librec.math.structure.SparseVector
Check if a vector contains a specific index
contains(int) - Method in class net.librec.recommender.item.RecommendedItemList
Returns true if this list contains the specified userIdx.
contains(int) - Method in interface net.librec.recommender.item.RecommendedList
Returns true if this list contains the specified userIdx.
contentEquals(InputStream, InputStream) - Static method in class net.librec.util.IOUtil
Compare the contents of two Streams to determine if they are equal or not.
contentEquals(Reader, Reader) - Static method in class net.librec.util.IOUtil
Compare the contents of two Readers to determine if they are equal or not.
context - Variable in class net.librec.data.model.AbstractDataModel
context
context - Variable in class net.librec.recommender.AbstractRecommender
RecommenderContext
context - Variable in class net.librec.recommender.TensorRecommender
RecommenderContext
copy(InputStream, OutputStream) - Static method in class net.librec.util.IOUtil
Copy bytes from an InputStream to an OutputStream.
copy(InputStream, Writer) - Static method in class net.librec.util.IOUtil
Copy bytes from an InputStream to chars on a Writer using the default character encoding of the platform.
copy(InputStream, Writer, String) - Static method in class net.librec.util.IOUtil
Copy bytes from an InputStream to chars on a Writer using the specified character encoding.
copy(Reader, Writer) - Static method in class net.librec.util.IOUtil
Copy chars from a Reader to a Writer.
copy(Reader, OutputStream) - Static method in class net.librec.util.IOUtil
Copy chars from a Reader to bytes on an OutputStream using the default character encoding of the platform, and calling flush.
copy(Reader, OutputStream, String) - Static method in class net.librec.util.IOUtil
Copy chars from a Reader to bytes on an OutputStream using the specified character encoding, and calling flush.
copyDirectory(String, String) - Static method in class net.librec.util.FileUtil
 
copyFile(String, String) - Static method in class net.librec.util.FileUtil
 
copyFile(File, File) - Static method in class net.librec.util.FileUtil
fast file copy
copyLarge(InputStream, OutputStream) - Static method in class net.librec.util.IOUtil
Copy bytes from a large (over 2GB) InputStream to an OutputStream.
copyLarge(Reader, Writer) - Static method in class net.librec.util.IOUtil
Copy chars from a large (over 2GB) Reader to a Writer.
CosineSimilarity - Class in net.librec.similarity
Cosine similarity
CosineSimilarity() - Constructor for class net.librec.similarity.CosineSimilarity
 
count - Variable in class net.librec.math.structure.SparseVector
 
cov() - Method in class net.librec.math.structure.DenseMatrix
 
CPCSimilarity - Class in net.librec.similarity
Constrained Pearson Correlation (CPC)
CPCSimilarity() - Constructor for class net.librec.similarity.CPCSimilarity
 
createItemNNs() - Method in class net.librec.recommender.cf.ranking.SLIMRecommender
Create item KNN list.
createItemSimilarityList() - Method in class net.librec.recommender.cf.ItemKNNRecommender
Create itemSimilarityList.
createUserSimilarityList() - Method in class net.librec.recommender.cf.UserKNNRecommender
Create userSimilarityList.

D

data - Variable in class net.librec.math.structure.DenseMatrix
read data
data - Variable in class net.librec.math.structure.DenseVector
 
data - Variable in class net.librec.math.structure.SparseVector
 
DataAppender - Interface in net.librec.data
A DataAppender is an interface to process and store appender data.
dataAppender - Variable in class net.librec.data.model.AbstractDataModel
Data Splitter DataAppender
DataContext - Class in net.librec.data
Data Context
DataContext() - Constructor for class net.librec.data.DataContext
 
DataContext(Configuration) - Constructor for class net.librec.data.DataContext
 
DataConvertor - Interface in net.librec.data
A DataConvertor is an interface to convert a data file from one source format to a target format.
dataConvertor - Variable in class net.librec.data.model.AbstractDataModel
The convertor of the model DataConvertor
dataConvertor - Variable in class net.librec.data.splitter.AbstractDataSplitter
dataConvertor
DataDriver - Class in net.librec.tool.driver
DataDriver
DataDriver() - Constructor for class net.librec.tool.driver.DataDriver
 
DataMatrix - Interface in net.librec.math.structure
Data Matrix
DataModel - Interface in net.librec.data
A DataModel represents a data access interface to the input file.
dataModel - Variable in class net.librec.recommender.RecommenderContext
 
DataSet - Interface in net.librec.math.structure
Data Set
DataSplitter - Interface in net.librec.data
A DataSplitter is an interface to split input data.
dataSplitter - Variable in class net.librec.data.model.AbstractDataModel
Data Splitter DataSplitter
DataSplitter.SplitterType - Enum in net.librec.data
The types of the splitter.
dataTable - Variable in class net.librec.math.structure.SparseStringMatrix
 
datetimeMatrix - Variable in class net.librec.data.convertor.AbstractDataConvertor
store time data as {user, item, rate} matrix
DateUtil - Class in net.librec.util
 
DateUtil() - Constructor for class net.librec.util.DateUtil
 
decay - Variable in class net.librec.recommender.AbstractRecommender
decay of learning rate
decay - Variable in class net.librec.recommender.TensorRecommender
decay of learning rate
deleteDirectory(String) - Static method in class net.librec.util.FileUtil
 
deleteDirectory(File) - Static method in class net.librec.util.FileUtil
 
deleteFile(String) - Static method in class net.librec.util.FileUtil
 
denormalize(double) - Method in class net.librec.recommender.SocialRecommender
denormalize a prediction to the region (minRate, maxRate)
DenseMatrix - Class in net.librec.math.structure
Data Structure: dense matrix
DenseMatrix(int, int) - Constructor for class net.librec.math.structure.DenseMatrix
Construct a dense matrix with specified dimensions
DenseMatrix(int, int, int) - Constructor for class net.librec.math.structure.DenseMatrix
Construct a dense matrix with specified dimensions
DenseMatrix(double[][]) - Constructor for class net.librec.math.structure.DenseMatrix
Construct a dense matrix by copying data from a given 2D array
DenseMatrix(double[][], int, int) - Constructor for class net.librec.math.structure.DenseMatrix
Construct a dense matrix by a shallow copy of a data array
DenseMatrix(DenseMatrix) - Constructor for class net.librec.math.structure.DenseMatrix
Construct a dense matrix by copying data from a given matrix
DenseVector - Class in net.librec.math.structure
Data Structure: dense vector
DenseVector(int) - Constructor for class net.librec.math.structure.DenseVector
Construct a dense vector with a specific size
DenseVector(double[]) - Constructor for class net.librec.math.structure.DenseVector
Construct a dense vector by deeply copying data from a given array
DenseVector(double[], boolean) - Constructor for class net.librec.math.structure.DenseVector
Construct a dense vector by copying data from a given array
DenseVector(DenseVector) - Constructor for class net.librec.math.structure.DenseVector
Construct a dense vector by deeply copying data from a given vector
deserialize(String) - Static method in class net.librec.util.FileUtil
 
DiagMatrix - Class in net.librec.math.structure
 
DiagMatrix(int, int, Table<Integer, Integer, Double>, Multimap<Integer, Integer>) - Constructor for class net.librec.math.structure.DiagMatrix
 
DiagMatrix(DiagMatrix) - Constructor for class net.librec.math.structure.DiagMatrix
 
DiceCoefficientSimilarity - Class in net.librec.similarity
Dice Coefficient Similarity
DiceCoefficientSimilarity() - Constructor for class net.librec.similarity.DiceCoefficientSimilarity
 
digamma(double) - Static method in class net.librec.math.algorithm.Gamma
digamma(x) = d log Gamma(x)/ dx
dim - Variable in class net.librec.math.structure.SymmMatrix
 
dimensions - Variable in class net.librec.math.structure.SparseTensor
 
dimensions() - Method in class net.librec.math.structure.SparseTensor
 
dimensions - Variable in class net.librec.recommender.TensorRecommender
dimensions indices
DIR_SEPARATOR - Static variable in class net.librec.util.IOUtil
The system directory separator character.
DIR_SEPARATOR_UNIX - Static variable in class net.librec.util.IOUtil
The Unix directory separator character.
DIR_SEPARATOR_WINDOWS - Static variable in class net.librec.util.IOUtil
The Windows directory separator character.
discrete(double[]) - Static method in class net.librec.math.algorithm.Randoms
Return a number from a discrete distribution: i with probability a[i].
DiversityEvaluator - Class in net.librec.eval.ranking
DiversityEvaluator, average dissimilarity of all pairs of items in the recommended list at a specific cutoff position.
DiversityEvaluator() - Constructor for class net.librec.eval.ranking.DiversityEvaluator
 
DocumentDataAppender - Class in net.librec.data.convertor.appender
A DocumentDataAppender is a class to process and store document appender data.
DocumentDataAppender() - Constructor for class net.librec.data.convertor.appender.DocumentDataAppender
 
doubles(int) - Static method in class net.librec.math.algorithm.Randoms
A random double array with values in [0, 1)
doubles(double, double, int) - Static method in class net.librec.math.algorithm.Randoms
A random double array with values in [min, max).
DriverClassUtil - Class in net.librec.util
Driver Class Util
DriverClassUtil() - Constructor for class net.librec.util.DriverClassUtil
 

E

EALSRecommender - Class in net.librec.recommender.cf.ranking
EALS: efficient Alternating Least Square for Weighted Regularized Matrix Factorization.
EALSRecommender() - Constructor for class net.librec.recommender.cf.ranking.EALSRecommender
 
earlyStop - Variable in class net.librec.recommender.AbstractRecommender
early-stop criteria
earlyStop - Variable in class net.librec.recommender.TensorRecommender
early-stop criteria
EFMRecommender - Class in net.librec.recommender.content
EFM Recommender Zhang Y, Lai G, Zhang M, et al.
EFMRecommender() - Constructor for class net.librec.recommender.content.EFMRecommender
 
empty(String) - Static method in class net.librec.util.FileUtil
empty a file content
EMPTY - Static variable in class net.librec.util.StringUtil
 
emptyStringArray - Static variable in class net.librec.util.StringUtil
 
entryIterator() - Method in class net.librec.recommender.item.RecommendedItemList
get the iterator of user-item-rating entry
entryIterator() - Method in interface net.librec.recommender.item.RecommendedList
get the iterator of user-item-rating entry
entryTopicDistribution - Variable in class net.librec.recommender.cf.ranking.AspectModelRecommender
{user, item, {topic z, probability}}
EPANECHNIKOV_KERNEL - Static variable in class net.librec.math.algorithm.KernelSmoothing
 
equals(Object) - Method in class net.librec.eval.Measure.MeasureValue
 
equals(Object) - Method in class net.librec.filter.GenericRecommendedFilter
 
equals(Object) - Method in class net.librec.recommender.item.ItemEntry
 
eStep() - Method in class net.librec.recommender.baseline.ItemClusterRecommender
 
eStep() - Method in class net.librec.recommender.baseline.UserClusterRecommender
 
eStep() - Method in class net.librec.recommender.cf.BHFreeRecommender
 
eStep() - Method in class net.librec.recommender.cf.BUCMRecommender
 
eStep() - Method in class net.librec.recommender.cf.ranking.AspectModelRecommender
 
eStep() - Method in class net.librec.recommender.cf.ranking.ItemBigramRecommender
 
eStep() - Method in class net.librec.recommender.cf.ranking.LDARecommender
 
eStep() - Method in class net.librec.recommender.cf.ranking.PLSARecommender
 
eStep() - Method in class net.librec.recommender.cf.rating.AspectModelRecommender
 
eStep() - Method in class net.librec.recommender.cf.rating.GPLSARecommender
 
eStep() - Method in class net.librec.recommender.cf.rating.LDCCRecommender
 
eStep() - Method in class net.librec.recommender.cf.rating.URPRecommender
 
eStep() - Method in class net.librec.recommender.ProbabilisticGraphicalRecommender
parameters estimation: used in the training phase
estimateParams() - Method in class net.librec.recommender.cf.BHFreeRecommender
 
estimateParams() - Method in class net.librec.recommender.cf.BUCMRecommender
 
estimateParams() - Method in class net.librec.recommender.cf.ranking.ItemBigramRecommender
 
estimateParams() - Method in class net.librec.recommender.cf.ranking.LDARecommender
 
estimateParams() - Method in class net.librec.recommender.cf.rating.AspectModelRecommender
 
estimateParams() - Method in class net.librec.recommender.cf.rating.LDCCRecommender
estimate the model parameters
estimateParams() - Method in class net.librec.recommender.cf.rating.URPRecommender
 
estimateParams() - Method in class net.librec.recommender.ProbabilisticGraphicalRecommender
estimate the model parameters
evaluate(RecommenderContext, RecommendedList) - Method in class net.librec.eval.AbstractRecommenderEvaluator
Evaluate on the recommender context with the recommended list.
evaluate(SparseMatrix, RecommendedList) - Method in class net.librec.eval.AbstractRecommenderEvaluator
Evaluate on the test set with the the list of recommended items.
evaluate(SparseMatrix, RecommendedList) - Method in class net.librec.eval.ranking.AUCEvaluator
Evaluate on the test set with the the list of recommended items.
evaluate(SparseMatrix, RecommendedList) - Method in class net.librec.eval.ranking.AveragePrecisionEvaluator
Evaluate on the test set with the the list of recommended items.
evaluate(SparseMatrix, RecommendedList) - Method in class net.librec.eval.ranking.AverageReciprocalHitRankEvaluator
Evaluate on the test set with the the list of recommended items.
evaluate(SparseMatrix, RecommendedList) - Method in class net.librec.eval.ranking.DiversityEvaluator
Evaluate on the test set with the the list of recommended items.
evaluate(SparseMatrix, RecommendedList) - Method in class net.librec.eval.ranking.HitRateEvaluator
Evaluate on the test set with the the list of recommended items.
evaluate(SparseMatrix, RecommendedList) - Method in class net.librec.eval.ranking.IdealDCGEvaluator
Evaluate on the test set with the the list of recommended items.
evaluate(SparseMatrix, RecommendedList) - Method in class net.librec.eval.ranking.NormalizedDCGEvaluator
Evaluate on the test set with the the list of recommended items.
evaluate(SparseMatrix, RecommendedList) - Method in class net.librec.eval.ranking.PrecisionEvaluator
Evaluate on the test set with the the list of recommended items.
evaluate(SparseMatrix, RecommendedList) - Method in class net.librec.eval.ranking.RecallEvaluator
Evaluate on the test set with the the list of recommended items.
evaluate(SparseMatrix, RecommendedList) - Method in class net.librec.eval.ranking.ReciprocalRankEvaluator
Evaluate on the test set with the the list of recommended items.
evaluate(SparseMatrix, RecommendedList) - Method in class net.librec.eval.rating.MAEEvaluator
 
evaluate(SparseMatrix, RecommendedList) - Method in class net.librec.eval.rating.MPEEvaluator
 
evaluate(SparseMatrix, RecommendedList) - Method in class net.librec.eval.rating.MSEEvaluator
 
evaluate(SparseMatrix, RecommendedList) - Method in class net.librec.eval.rating.RMSEEvaluator
 
evaluate(RecommenderContext, RecommendedList) - Method in interface net.librec.eval.RecommenderEvaluator
Evaluate on the recommender context with the recommended list.
evaluate(RecommenderEvaluator) - Method in class net.librec.recommender.AbstractRecommender
evaluate
evaluate(RecommenderEvaluator) - Method in interface net.librec.recommender.Recommender
evaluate
evaluate(RecommenderEvaluator) - Method in class net.librec.recommender.TensorRecommender
 
evaluateMap() - Method in class net.librec.recommender.AbstractRecommender
evaluate Map
evaluateMap() - Method in interface net.librec.recommender.Recommender
evaluate Map
evaluateMap() - Method in class net.librec.recommender.TensorRecommender
 
except(List<T>, List<T>) - Static method in class net.librec.util.Lists
Note: if you need to operate on the original list, it's better to use the method "retainAll" or "removeAll"
exceptSize(List<T>, List<T>) - Static method in class net.librec.util.Lists
 
exist(String) - Static method in class net.librec.util.FileUtil
check whether a file exists
ExJaccardSimilarity - Class in net.librec.similarity
Extend Jaccard Coefficient
ExJaccardSimilarity() - Constructor for class net.librec.similarity.ExJaccardSimilarity
 
exp(double) - Static method in class net.librec.math.algorithm.Randoms
Return a real number from an exponential distribution with rate lambda.
ExternalRecommender - Class in net.librec.recommender.ext
Suppose that you have some predictive ratings (in "pred.txt") generated by an external recommender (e.g., some recommender of MyMediaLite).
ExternalRecommender() - Constructor for class net.librec.recommender.ext.ExternalRecommender
 
eye(int) - Static method in class net.librec.math.structure.DenseMatrix
Construct an identity matrix
eye(int) - Static method in class net.librec.math.structure.DiagMatrix
 

F

fabonacci(int) - Static method in class net.librec.math.algorithm.Maths
Fabonacci sequence.
factorial(int) - Static method in class net.librec.math.algorithm.Maths
Return n!
FactorizationMachineRecommender - Class in net.librec.recommender
Factorization Machine Recommender Rendle, Steffen, et al., Fast Context-aware Recommendations with Factorization Machines, SIGIR, 2011.
FactorizationMachineRecommender() - Constructor for class net.librec.recommender.FactorizationMachineRecommender
 
FAILED - Static variable in class net.librec.job.JobStatus
 
featureFactor - Variable in class net.librec.recommender.content.EFMRecommender
 
featureMatrix - Variable in class net.librec.recommender.content.EFMRecommender
 
fiber(int, int...) - Method in class net.librec.math.structure.SparseTensor
A fiber is defined by fixing every index but one.
FILE_SEPARATOR - Static variable in class net.librec.util.Systems
 
FileUtil - Class in net.librec.util
 
FileUtil.Converter<K,T> - Interface in net.librec.util
Transform an input object with Type K to an output object with type T
FileUtil.MapWriter<K,V> - Interface in net.librec.util
interface for converting an entry of a map to string
filter(List<RecommendedItem>) - Method in class net.librec.filter.GenericRecommendedFilter
Filter the recommended list.
filter(List<RecommendedItem>) - Method in interface net.librec.filter.RecommendedFilter
Filter the recommended list.
FISMaucRecommender - Class in net.librec.recommender.cf.ranking
Kabbur et al., FISM: Factored Item Similarity Models for Top-N Recommender Systems, KDD 2013.
FISMaucRecommender() - Constructor for class net.librec.recommender.cf.ranking.FISMaucRecommender
 
FISMrmseRecommender - Class in net.librec.recommender.cf.ranking
Kabbur et al., FISM: Factored Item Similarity Models for Top-N Recommender Systems, KDD 2013.
FISMrmseRecommender() - Constructor for class net.librec.recommender.cf.ranking.FISMrmseRecommender
 
FMALSRecommender - Class in net.librec.recommender.cf.rating
Factorization Machine Recommender via Alternating Least Square
FMALSRecommender() - Constructor for class net.librec.recommender.cf.rating.FMALSRecommender
 
FMSGDRecommender - Class in net.librec.recommender.cf.rating
Stochastic Gradient Descent with Square Loss Rendle, Steffen, "Factorization Machines", Proceedings of the 10th IEEE International Conference on Data Mining, 2010 Rendle, Steffen, "Factorization Machines with libFM", ACM Transactions on Intelligent Systems and Technology, 2012
FMSGDRecommender() - Constructor for class net.librec.recommender.cf.rating.FMSGDRecommender
 
formatBytes(long) - Static method in class net.librec.util.FileUtil
Returns a human-readable version of the file size, where the input represents a specific number of bytes.
formatSize(long) - Static method in class net.librec.util.FileUtil
Returns a human-readable version of the file size.

G

Gamma - Class in net.librec.math.algorithm
 
Gamma() - Constructor for class net.librec.math.algorithm.Gamma
 
gamma(double) - Static method in class net.librec.math.algorithm.Gamma
The Gamma function is defined by:
gamma(double, double) - Static method in class net.librec.math.algorithm.Randoms
Randomly sample 1 point from Gamma Distribution with the given parameters.
GammaDenseMatrix(int, int) - Constructor for class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrix
 
GammaDenseMatrixGR(int, int) - Constructor for class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrixGR
 
GammaDenseVector(int) - Constructor for class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseVector
 
Gaussian - Class in net.librec.math.algorithm
Gaussian
Gaussian() - Constructor for class net.librec.math.algorithm.Gaussian
 
gaussian(double, double, double) - Method in class net.librec.math.algorithm.Maths
Return a gaussian value with mean mu and standard deviation sigma.
gaussian(double, double) - Static method in class net.librec.math.algorithm.Randoms
Return a real number from a Gaussian distribution with given mean and stddev.
gaussian(double, double, double) - Method in class net.librec.recommender.ext.PersonalityDiagnosisRecommender
 
GAUSSIAN_KERNEL - Static variable in class net.librec.math.algorithm.KernelSmoothing
 
GBPRRecommender - Class in net.librec.recommender.cf.ranking
Pan and Chen, GBPR: Group Preference Based Bayesian Personalized Ranking for One-Class Collaborative Filtering, IJCAI 2013.
GBPRRecommender() - Constructor for class net.librec.recommender.cf.ranking.GBPRRecommender
 
gcd(int, int) - Static method in class net.librec.math.algorithm.Maths
Greatest common divisor (gcd) or greatest common factor (gcf)
generateNewJobId() - Static method in class net.librec.util.JobUtil
generate a new job id.
GenericPreference - Class in net.librec.data.preference
Deprecated.
GenericPreference() - Constructor for class net.librec.data.preference.GenericPreference
Deprecated.
 
GenericRecommendedFilter - Class in net.librec.filter
Recommended Filter
GenericRecommendedFilter() - Constructor for class net.librec.filter.GenericRecommendedFilter
 
GenericRecommendedItem - Class in net.librec.recommender.item
Generic Recommended Item
GenericRecommendedItem(String, String, double) - Constructor for class net.librec.recommender.item.GenericRecommendedItem
 
get(String) - Method in class net.librec.conf.Configuration
 
get(String, String) - Method in class net.librec.conf.Configuration
 
get(int, int) - Method in interface net.librec.math.structure.DataMatrix
Retrieve value at entry [row, column]
get(int, int) - Method in class net.librec.math.structure.DenseMatrix
Get the value at entry [row, column]
get(int) - Method in class net.librec.math.structure.DenseVector
Get a value at entry [index]
get() - Method in interface net.librec.math.structure.MatrixEntry
Returns the value at the current index
get(int, int) - Method in class net.librec.math.structure.SparseMatrix
Retrieve value at entry [row, column]
get(int, int) - Method in class net.librec.math.structure.SparseStringMatrix
Retrieve value at entry [row, column]
get(int...) - Method in class net.librec.math.structure.SparseTensor
Return a value given a specific i-entry.
get(int) - Method in class net.librec.math.structure.SparseVector
Retrieve a value at entry [idx]
get(int, int) - Method in class net.librec.math.structure.SymmMatrix
Get a value at entry (row, col)
get() - Method in interface net.librec.math.structure.TensorEntry
 
get() - Method in interface net.librec.math.structure.VectorEntry
Returns the value at the current index
getAllFeatureIds() - Method in class net.librec.data.convertor.ArffDataConvertor
Return user, item, appender {raw id, inner id} mapping
getAttributes() - Method in class net.librec.data.convertor.ArffDataConvertor
Return the attributes the input data.
getBoolean(String) - Method in class net.librec.conf.Configuration
 
getBoolean(String, boolean) - Method in class net.librec.conf.Configuration
 
getCapacity() - Method in class net.librec.math.structure.SparseVector
 
getClass(String) - Static method in class net.librec.util.DriverClassUtil
get Class by driver name.
getClassByName(String) - Method in class net.librec.conf.Configuration
Load a class by name.
getClassByName(String, String) - Method in class net.librec.conf.Configuration
Load a class by name.
getColumnIndices() - Method in class net.librec.math.structure.SparseMatrix
 
getColumnIndices() - Method in class net.librec.math.structure.SparseStringMatrix
 
getColumns(int) - Method in class net.librec.math.structure.SparseMatrix
get columns of a specific row where (row, column) entries are non-zero
getColumnSet() - Method in class net.librec.data.model.ArffAttribute
Return attribute column set.
getColumnsSet(int) - Method in class net.librec.math.structure.SparseMatrix
get columns of a specific row where (row, column) entries are non-zero
getConf() - Method in class net.librec.common.AbstractContext
 
getConf() - Method in interface net.librec.common.LibrecContext
get Configuration
getConf() - Method in interface net.librec.conf.Configurable
 
getConf() - Method in class net.librec.conf.Configured
 
getConf() - Method in class net.librec.eval.AbstractRecommenderEvaluator
Return the configuration fo the evaluator.
getContext() - Method in interface net.librec.data.DataModel
Get data Context.
getContext() - Method in class net.librec.data.model.AbstractDataModel
Get data context.
getContext() - Method in class net.librec.recommender.AbstractRecommender
get Context
getCorrelation(SparseVector, SparseVector) - Method in class net.librec.similarity.AbstractRecommenderSimilarity
Find the common rated items by this user and that user, or the common users have rated this item or that item.
getCorrelation(SparseVector, SparseVector) - Method in class net.librec.similarity.BinaryCosineSimilarity
Get the binary cosine similarity of two sparse vectors.
getCorrelation(SparseVector, SparseVector) - Method in class net.librec.similarity.JaccardSimilarity
Find the common rated items by this user and that user, or the common users have rated this item or that item.
getCorrelation(SparseVector, SparseVector) - Method in class net.librec.similarity.KRCCSimilarity
Find the common rated items by this user and that user, or the common users have rated this item or that item.
getCount() - Method in class net.librec.math.structure.SparseVector
Number of entries in the sparse structure
getCurrentFolder() - Static method in class net.librec.util.FileUtil
 
getCurrentPath() - Static method in class net.librec.util.FileUtil
 
getData() - Method in class net.librec.math.structure.DenseMatrix
 
getData() - Method in class net.librec.math.structure.DenseVector
 
getData() - Method in class net.librec.math.structure.SparseMatrix
 
getData() - Method in class net.librec.math.structure.SparseStringMatrix
 
getData() - Method in class net.librec.math.structure.SparseVector
 
getData() - Method in class net.librec.math.structure.SymmMatrix
 
getDataAppender() - Method in interface net.librec.data.DataModel
Get data appender.
getDataAppender() - Method in class net.librec.data.model.AbstractDataModel
Get data appender.
getDataFileRate() - Method in class net.librec.data.convertor.TextDataConvertor
Return rate of alreadyLoaded/allData in one file.
getDataModel() - Method in class net.librec.recommender.AbstractRecommender
get Data Model
getDataModel() - Method in interface net.librec.recommender.Recommender
get DataModel
getDataModel() - Method in class net.librec.recommender.RecommenderContext
 
getDataModel() - Method in class net.librec.recommender.TensorRecommender
 
getDataModelClass() - Method in class net.librec.job.RecommenderJob
Get data model class.
getDataSplitter() - Method in interface net.librec.data.DataModel
Get data splitter.
getDataSplitter() - Method in class net.librec.data.model.AbstractDataModel
Get data splitter.
getDataTable() - Method in class net.librec.math.structure.SparseMatrix
 
getDateFormat(String) - Static method in class net.librec.util.DateUtil
Create a new object with the given format
getDatetimeDataSet() - Method in interface net.librec.data.DataModel
Get datetime data set.
getDatetimeDataSet() - Method in class net.librec.data.model.ArffDataModel
 
getDatetimeDataSet() - Method in class net.librec.data.model.JDBCDataModel
 
getDatetimeDataSet() - Method in class net.librec.data.model.TextDataModel
Get datetime data set.
getDatetimeMatrix() - Method in class net.librec.data.convertor.AbstractDataConvertor
Return the date matrix.
getDatetimeMatrix() - Method in interface net.librec.data.DataConvertor
Returns a SparseMatrix object which stores time data.
getDesktop() - Static method in class net.librec.util.Systems
 
getDim() - Method in class net.librec.math.structure.SymmMatrix
 
getDouble(String, Double) - Method in class net.librec.conf.Configuration
 
getDouble(String) - Method in class net.librec.conf.Configuration
 
getDriverName(String) - Static method in class net.librec.util.DriverClassUtil
get Driver Name by clazz
getDriverName(Class<? extends Recommender>) - Static method in class net.librec.util.DriverClassUtil
get Driver Name by clazz
getEntryValue(int, int) - Method in class net.librec.recommender.item.RecommendedItemList
Deprecated.
getEntryValue(int, int) - Method in interface net.librec.recommender.item.RecommendedList
Deprecated.
getEvaluatorClass() - Method in enum net.librec.eval.Measure
Return the Class object of the evaluator.
getEvaluatorClass(String) - Method in class net.librec.job.RecommenderJob
Get evaluator class.
getFilePathRate() - Method in class net.librec.data.convertor.TextDataConvertor
Return rate of loading files in data directory.
getFilterClass() - Method in class net.librec.job.RecommenderJob
Get filter class.
getFinishTime() - Method in class net.librec.job.JobStatus
 
getFixedRatioByUser(double) - Method in class net.librec.data.splitter.RatioDataSplitter
Split ratings into two parts: the training set consisting of user-item ratings where a fixed number of ratings corresponding to the given ratio are preserved for each user as training data with the rest as test.
getFloat(String, Float) - Method in class net.librec.conf.Configuration
 
getFloat(String) - Method in class net.librec.conf.Configuration
 
getGivenNByItem(int) - Method in class net.librec.data.splitter.GivenNDataSplitter
Split ratings into two parts: the training set consisting of user-item ratings where numGiven ratings are preserved for each item, and the rest are used as the testing data.
getGivenNByItemDate(int) - Method in class net.librec.data.splitter.GivenNDataSplitter
Split ratings into two parts: the training set consisting of user-item ratings where numGiven earliest ratings are preserved for each item, and the rest are used as the testing data.
getGivenNByUser(int) - Method in class net.librec.data.splitter.GivenNDataSplitter
Split ratings into two parts: the training set consisting of user-item ratings where numGiven ratings are preserved for each user, and the rest are used as the testing data.
getGivenNByUserDate(int) - Method in class net.librec.data.splitter.GivenNDataSplitter
Split ratings into two parts: the training set consisting of user-item ratings where numGiven earliest ratings are preserved for each user, and the rest are used as the testing data.
getIndex() - Method in class net.librec.data.model.ArffAttribute
Return attribute index.
getIndex(int, int) - Method in class net.librec.math.structure.SparseTensor
Return indices (positions) of a key in dimension d.
getIndex() - Method in class net.librec.math.structure.SparseVector
 
getIndexDimension(int) - Method in class net.librec.math.structure.SparseTensor
 
getIndexList() - Method in class net.librec.math.structure.SparseVector
 
getIndexSet() - Method in class net.librec.math.structure.SparseVector
 
getIndices(int, int) - Method in class net.librec.math.structure.SparseTensor
Return all entries for a (user, item) pair
getInstances() - Method in class net.librec.data.convertor.ArffDataConvertor
Return the instances of the input data.
getInt(String, Integer) - Method in class net.librec.conf.Configuration
 
getInt(String) - Method in class net.librec.conf.Configuration
 
getInts(String) - Method in class net.librec.conf.Configuration
Get the value of the name property as a set of comma-delimited int values.
getIP() - Static method in class net.librec.util.Systems
Get IP of the System.
getItem() - Method in class net.librec.util.RatingContext
Get the item index of the context.
getItemAnchor() - Method in class net.librec.recommender.cf.rating.LLORMAUpdater
Getter method for anchor item of this local model.
getItemAppender() - Method in class net.librec.data.convertor.appender.SocialDataAppender
Get item appender.
getItemDimension() - Method in class net.librec.math.structure.SparseTensor
 
getItemId(String) - Method in class net.librec.data.convertor.TextDataConvertor
Return an item's inner id by its raw id.
getItemId() - Method in class net.librec.recommender.item.GenericRecommendedItem
 
getItemId() - Method in interface net.librec.recommender.item.RecommendedItem
 
getItemIds() - Method in class net.librec.data.convertor.ArffDataConvertor
Return item {rawid, inner id} mappings
getItemIds() - Method in class net.librec.data.convertor.TextDataConvertor
Return item {rawid, inner id} mappings
getItemIdx() - Method in class net.librec.recommender.item.UserItemRatingEntry
 
getItemIdxListByUserIdx(int) - Method in class net.librec.recommender.item.RecommendedItemList
Returns the itemEntry of user index in this list.
getItemIdxListByUserIdx(int) - Method in interface net.librec.recommender.item.RecommendedList
get ItemIdxList By UserIdx
getItemMappingData() - Method in interface net.librec.data.DataModel
Get item mapping data.
getItemMappingData() - Method in class net.librec.data.model.ArffDataModel
Get item mapping data.
getItemMappingData() - Method in class net.librec.data.model.JDBCDataModel
 
getItemMappingData() - Method in class net.librec.data.model.TextDataModel
Get item mapping data.
getJobId() - Method in class net.librec.job.JobStatus
 
getJobRunState(int) - Static method in class net.librec.job.JobStatus
Helper method to get human-readable state of the job.
getJobStage() - Method in class net.librec.job.JobStatus
 
getJobStatus() - Method in class net.librec.job.progress.ProgressReporter
 
getKey() - Method in class net.librec.recommender.item.ItemEntry
 
getLoadAllFileRate() - Method in class net.librec.data.convertor.TextDataConvertor
Return rate of alreadyLoaded/allData in all files.
getLocalItemFactors() - Method in class net.librec.recommender.cf.rating.LLORMAUpdater
Getter method for item profile of this local model.
getLocalUserFactors() - Method in class net.librec.recommender.cf.rating.LLORMAUpdater
Getter method for user profile of this local model.
getLong(String, Long) - Method in class net.librec.conf.Configuration
 
getLong(String) - Method in class net.librec.conf.Configuration
 
getLOOByItems() - Method in class net.librec.data.splitter.LOOCVDataSplitter
Split ratings into two parts where one rating per item is preserved as the test set and the remaining data as the training set.
getLooByItemsDate() - Method in class net.librec.data.splitter.LOOCVDataSplitter
Split ratings into two parts where the last item according to date is preserved as the test set and the remaining data as the training set.
getLOOByUser() - Method in class net.librec.data.splitter.LOOCVDataSplitter
Split ratings into two parts where one rating per user is preserved as the test set and the remaining data as the training set.
getLOOByUserDate() - Method in class net.librec.data.splitter.LOOCVDataSplitter
Split ratings into two parts where the last user according to date is preserved as the test set and the remaining data as the training set.
getMeasure() - Method in class net.librec.eval.Measure.MeasureValue
Return the Measure object of the MeasureValue object
getMeasureEnumList(boolean, int) - Static method in enum net.librec.eval.Measure
 
getName() - Method in class net.librec.conf.Configuration.Resource
 
getName() - Method in class net.librec.data.model.ArffAttribute
Return attribute name.
getOs() - Static method in class net.librec.util.Systems
Get OS type of the System.
getPhi(DenseMatrix, int, DenseMatrix, int, int) - Method in class net.librec.recommender.cf.rating.BPoissMFRecommender
 
getPreferenceMatrix() - Method in class net.librec.data.convertor.AbstractDataConvertor
Return the rate matrix.
getPreferenceMatrix() - Method in interface net.librec.data.DataConvertor
Returns a SparseMatrix object which stores rate data.
getProgress() - Method in class net.librec.job.JobStatus
 
getRank() - Method in class net.librec.recommender.cf.rating.LLORMAUpdater
Getter method for rank of this local model.
getRatio(double, double) - Method in class net.librec.data.splitter.RatioDataSplitter
Split the rating into : (train-ratio) training, (validation-ratio) validation, and test three subsets.
getRatioByItem(double) - Method in class net.librec.data.splitter.RatioDataSplitter
Split ratings into two parts: the training set consisting of user-item ratings where ratio percentage of ratings are preserved for each item, and the rest are used as the testing data.
getRatioByItemDate(double) - Method in class net.librec.data.splitter.RatioDataSplitter
Split the ratings of each item (by date) into two parts: (ratio) training, (1-ratio) test subsets.
getRatioByRating(double) - Method in class net.librec.data.splitter.RatioDataSplitter
Split ratings into two parts: (ratio) training, (1-ratio) test subsets.
getRatioByRatingDate(double) - Method in class net.librec.data.splitter.RatioDataSplitter
Split the ratings (by date) into two parts: (ratio) training, (1-ratio) test subsets.
getRatioByUser(double) - Method in class net.librec.data.splitter.RatioDataSplitter
Split ratings into two parts: the training set consisting of user-item ratings where ratio percentage of ratings are preserved for each user, and the rest are used as the testing data.
getRatioByUserDate(double) - Method in class net.librec.data.splitter.RatioDataSplitter
Split the ratings of each user (by date) into two parts: (ratio) training, (1-ratio) test subsets
getReader(String) - Static method in class net.librec.util.FileUtil
Return the BufferedReader List of files in a specified directory.
getReader(File) - Static method in class net.librec.util.FileUtil
Get reader of a given file.
getRecommendedList() - Method in class net.librec.recommender.AbstractRecommender
get Recommended List
getRecommendedList() - Method in interface net.librec.recommender.Recommender
get Recommended List
getRecommendedList() - Method in class net.librec.recommender.TensorRecommender
 
getRecommenderClass() - Method in class net.librec.job.RecommenderJob
Get recommender class.
getRelationName() - Method in class net.librec.data.convertor.ArffDataConvertor
Return the relation name of input data.
getRelevantKeys(int, int, int) - Method in class net.librec.math.structure.SparseTensor
Return keys in a target dimension td related with a key in dimension sd.
getResource(String) - Method in class net.librec.conf.Configuration
 
getResource() - Method in class net.librec.conf.Configuration.Resource
 
getResource(String) - Static method in class net.librec.util.FileUtil
Get resource path, supporting file and url io path
getRowPointers() - Method in class net.librec.math.structure.SparseMatrix
 
getRowPointers() - Method in class net.librec.math.structure.SparseStringMatrix
 
getRows(int) - Method in class net.librec.math.structure.SparseMatrix
get rows of a specific column where (row, column) entries are non-zero
getRows(int) - Method in class net.librec.math.structure.SparseStringMatrix
get rows of a specific column where (row, column) entries are non-zero
getRowsSet(int) - Method in class net.librec.math.structure.SparseMatrix
get rows of a specific column where (row, column) entries are non-zero
getS() - Method in class net.librec.math.algorithm.SVD
Return the diagonal matrix of singular values
getSimilarities() - Method in class net.librec.recommender.RecommenderContext
 
getSimilarity() - Method in class net.librec.recommender.RecommenderContext
 
getSimilarity(List<? extends Number>, List<? extends Number>) - Method in class net.librec.similarity.AbstractRecommenderSimilarity
Calculate the similarity between thisList and thatList.
getSimilarity(List<? extends Number>, List<? extends Number>) - Method in class net.librec.similarity.BinaryCosineSimilarity
 
getSimilarity(List<? extends Number>, List<? extends Number>) - Method in class net.librec.similarity.CosineSimilarity
calculate the similarity between thisList and thatList.
getSimilarity(List<? extends Number>, List<? extends Number>) - Method in class net.librec.similarity.CPCSimilarity
Calculate the similarity between thisList and thatList.
getSimilarity(List<? extends Number>, List<? extends Number>) - Method in class net.librec.similarity.DiceCoefficientSimilarity
Calculate the similarity between thisList and thatList.
getSimilarity(List<? extends Number>, List<? extends Number>) - Method in class net.librec.similarity.ExJaccardSimilarity
Calculate the similarity between thisList and thatList.
getSimilarity(List<? extends Number>, List<? extends Number>) - Method in class net.librec.similarity.JaccardSimilarity
 
getSimilarity(List<? extends Number>, List<? extends Number>) - Method in class net.librec.similarity.KRCCSimilarity
Calculate the similarity between thisList and thatList.
getSimilarity(List<? extends Number>, List<? extends Number>) - Method in class net.librec.similarity.MSDSimilarity
Calculate the similarity between thisList and thatList.
getSimilarity(List<? extends Number>, List<? extends Number>) - Method in class net.librec.similarity.MSESimilarity
Calculate the similarity between thisList and thatList.
getSimilarity(List<? extends Number>, List<? extends Number>) - Method in class net.librec.similarity.PCCSimilarity
Calculate the similarity between thisList and thatList.
getSimilarityClass() - Method in class net.librec.job.RecommenderJob
Get similarity class
getSimilarityMatrix() - Method in class net.librec.similarity.AbstractRecommenderSimilarity
Return the similarity matrix.
getSimilarityMatrix() - Method in interface net.librec.similarity.RecommenderSimilarity
get similarity matrix as a SymmMatrix
getSingularValues() - Method in class net.librec.math.algorithm.SVD
Return the one-dimensional array of singular values
getSize() - Method in class net.librec.recommender.item.RecommendedItemList
the number of users (the number of ArrayList)
getSparseTensor() - Method in class net.librec.data.convertor.AbstractDataConvertor
Return the rate tensor.
getSparseTensor() - Method in interface net.librec.data.DataConvertor
Returns a SparseTensor object which stores rate data.
getStartTime() - Method in class net.librec.job.JobStatus
 
getStringCollection(String) - Static method in class net.librec.util.StringUtil
Returns a collection of strings.
getStringCollection(String, String) - Static method in class net.librec.util.StringUtil
Returns a collection of strings.
getStrings(String) - Method in class net.librec.conf.Configuration
Get the comma delimited values of the name property as an array of Strings.
getStrings(String) - Static method in class net.librec.util.StringUtil
Returns an arraylist of strings.
getSubMatrix(int, int, int, int) - Method in class net.librec.math.structure.DenseMatrix
Return a sub matrix of this matrix.
getTargetKeyFromSubKey(Integer[]) - Method in class net.librec.math.structure.SparseTensor
 
getTestData() - Method in interface net.librec.data.DataSplitter
Get test data.
getTestData() - Method in class net.librec.data.splitter.AbstractDataSplitter
(non-Javadoc)
getTestDataSet() - Method in interface net.librec.data.DataModel
Get test data set.
getTestDataSet() - Method in class net.librec.data.model.AbstractDataModel
Get test data set.
getThreadId() - Method in class net.librec.recommender.cf.rating.LLORMAUpdater
Getter method for thread ID.
getTopN() - Method in class net.librec.eval.Measure.MeasureValue
Return the number of items in the recommended list.
getTrainData() - Method in interface net.librec.data.DataSplitter
Get train data.
getTrainData() - Method in class net.librec.data.splitter.AbstractDataSplitter
(non-Javadoc)
getTrainDataSet() - Method in interface net.librec.data.DataModel
Get train data set.
getTrainDataSet() - Method in class net.librec.data.model.AbstractDataModel
Get train data set.
getTrimmedStrings(String) - Method in class net.librec.conf.Configuration
Get the comma delimited values of the name property as an array of Strings, trimmed of the leading and trailing whitespace.
getTrimmedStrings(String) - Static method in class net.librec.util.StringUtil
Splits a comma separated value String, trimming leading and trailing whitespace on each value.
getType() - Method in class net.librec.data.model.ArffAttribute
Return attribute type.
getTypeByIndex(int) - Method in class net.librec.data.model.ArffInstance
Get attribute type by index.
getU() - Method in class net.librec.math.algorithm.SVD
Return the left singular vectors
getUser() - Method in class net.librec.util.RatingContext
Get the user index of the context.
getUserAnchor() - Method in class net.librec.recommender.cf.rating.LLORMAUpdater
Getter method for anchor user of this local model.
getUserAppender() - Method in class net.librec.data.convertor.appender.SocialDataAppender
Get user appender.
getUserDimension() - Method in class net.librec.math.structure.SparseTensor
 
getUserId(String) - Method in class net.librec.data.convertor.TextDataConvertor
Return a user's inner id by his raw id.
getUserId() - Method in class net.librec.recommender.item.GenericRecommendedItem
 
getUserId() - Method in interface net.librec.recommender.item.RecommendedItem
 
getUserIds() - Method in class net.librec.data.convertor.ArffDataConvertor
Return user {rawid, inner id} mappings
getUserIds() - Method in class net.librec.data.convertor.TextDataConvertor
Return user {rawid, inner id} mappings
getUserIdx() - Method in class net.librec.recommender.item.UserItemRatingEntry
 
getUserMappingData() - Method in interface net.librec.data.DataModel
Get user mapping data.
getUserMappingData() - Method in class net.librec.data.model.ArffDataModel
Get user mapping data.
getUserMappingData() - Method in class net.librec.data.model.JDBCDataModel
 
getUserMappingData() - Method in class net.librec.data.model.TextDataModel
Get user mapping data.
getV() - Method in class net.librec.math.algorithm.SVD
Return the right singular vectors
getValidData() - Method in interface net.librec.data.DataSplitter
Get valid data.
getValidData() - Method in class net.librec.data.splitter.AbstractDataSplitter
(non-Javadoc)
getValidDataSet() - Method in interface net.librec.data.DataModel
Get valid data set.
getValidDataSet() - Method in class net.librec.data.model.AbstractDataModel
Get valid data set.
getValue() - Method in class net.librec.recommender.item.GenericRecommendedItem
 
getValue() - Method in class net.librec.recommender.item.ItemEntry
 
getValue() - Method in interface net.librec.recommender.item.RecommendedItem
 
getValue() - Method in class net.librec.recommender.item.UserItemRatingEntry
 
getValueByAttrName(String) - Method in class net.librec.data.model.ArffInstance
Get data value by the attribute name.
getValueByIndex(int) - Method in class net.librec.data.model.ArffInstance
Get data value by index.
getValueSet() - Method in class net.librec.math.structure.SparseMatrix
 
getWriter(String) - Static method in class net.librec.util.FileUtil
Get writer of a given path.
getWriter(File) - Static method in class net.librec.util.FileUtil
Get writer of a given file.
GivenNDataSplitter - Class in net.librec.data.splitter
GivenN Data Splitter
Split dataset into train set and test set by given number.
GivenNDataSplitter() - Constructor for class net.librec.data.splitter.GivenNDataSplitter
Empty constructor.
GivenNDataSplitter(DataConvertor, Configuration) - Constructor for class net.librec.data.splitter.GivenNDataSplitter
Initializes a newly created GivenNDataSplitter object with configuration.
GivenTestSetDataSplitter - Class in net.librec.data.splitter
Given Test Set Data Splitter
Get test set from specified path
Test set and train set should be in the same directory.
GivenTestSetDataSplitter() - Constructor for class net.librec.data.splitter.GivenTestSetDataSplitter
Empty constructor.
GivenTestSetDataSplitter(DataConvertor, Configuration) - Constructor for class net.librec.data.splitter.GivenTestSetDataSplitter
Initializes a newly created GivenTestSetDataSplitter object with configuration.
GlobalAverageRecommender - Class in net.librec.recommender.baseline
Baseline: predict by average rating of all users
GlobalAverageRecommender() - Constructor for class net.librec.recommender.baseline.GlobalAverageRecommender
 
globalMean - Variable in class net.librec.recommender.AbstractRecommender
global mean of ratings
globalMean - Variable in class net.librec.recommender.MatrixFactorizationRecommender
global mean
globalMean - Variable in class net.librec.recommender.TensorRecommender
global mean of ratings
globalRegItem - Variable in class net.librec.recommender.cf.rating.LLORMARecommender
 
globalRegUser - Variable in class net.librec.recommender.cf.rating.LLORMARecommender
 
golden_ratio - Static variable in class net.librec.math.algorithm.Maths
Golden ratio: http://en.wikipedia.org/wiki/Golden_ratio
GPLSARecommender - Class in net.librec.recommender.cf.rating
Thomas Hofmann, Collaborative Filtering via Gaussian Probabilistic Latent Semantic Analysis, SIGIR 2003.
GPLSARecommender() - Constructor for class net.librec.recommender.cf.rating.GPLSARecommender
 

H

hadamardProduct(DenseMatrix, DenseMatrix) - Static method in class net.librec.math.structure.DenseMatrix
Return Hadamard product of two matrices.
hashCode() - Method in class net.librec.eval.Measure.MeasureValue
 
hashCode() - Method in class net.librec.filter.GenericRecommendedFilter
 
hashCode() - Method in class net.librec.recommender.item.ItemEntry
 
HFTRecommender - Class in net.librec.recommender.content
HFT Recommender McAuley J, Leskovec J.
HFTRecommender() - Constructor for class net.librec.recommender.content.HFTRecommender
 
HFTRecommender(SparseMatrix, SparseMatrix, int) - Constructor for class net.librec.recommender.content.HFTRecommender
 
HitRateEvaluator - Class in net.librec.eval.ranking
HitRateEvaluator
HitRateEvaluator() - Constructor for class net.librec.eval.ranking.HitRateEvaluator
 
hMean(double, double) - Static method in class net.librec.math.algorithm.Stats
Return harmonic mean.
HybridRecommender - Class in net.librec.recommender.hybrid
Zhou et al., Solving the apparent diversity-accuracy dilemma of recommender systems, Proceedings of the National Academy of Sciences, 2010.
HybridRecommender() - Constructor for class net.librec.recommender.hybrid.HybridRecommender
 
hypot(double, double) - Static method in class net.librec.math.algorithm.Maths
sqrt(a^2 + b^2) without under/overflow.

I

IdealDCGEvaluator - Class in net.librec.eval.ranking
IdealDCGEvaluator
IdealDCGEvaluator() - Constructor for class net.librec.eval.ranking.IdealDCGEvaluator
 
impItemFactors - Variable in class net.librec.recommender.cf.rating.ASVDPlusPlusRecommender
 
impItemFactors - Variable in class net.librec.recommender.cf.rating.SVDPlusPlusRecommender
item implicit feedback factors, "imp" string means implicit
index - Variable in class net.librec.math.structure.SparseVector
 
index() - Method in interface net.librec.math.structure.VectorEntry
Returns the current index
indexs(int, int, int) - Static method in class net.librec.math.algorithm.Randoms
Generate no repeat size indexes from min to max
init(double, double) - Method in class net.librec.math.structure.DenseMatrix
Initialize a dense matrix with small Guassian values
init(double) - Method in class net.librec.math.structure.DenseMatrix
Initialize a dense matrix with small random values in (0, range)
init() - Method in class net.librec.math.structure.DenseMatrix
Initialize a dense matrix with small random values in (0, 1)
init(double, double) - Method in class net.librec.math.structure.DenseVector
Initialize a dense vector with Gaussian values
init() - Method in class net.librec.math.structure.DenseVector
Initialize a dense vector with uniform values in (0, 1)
init(double) - Method in class net.librec.math.structure.DenseVector
Initialize a dense vector with uniform values in (0, range)
init() - Method in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrix
 
init() - Method in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrixGR
 
init() - Method in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseVector
 
init2(double) - Method in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseVector
 
initAlpha - Variable in class net.librec.recommender.cf.ranking.ItemBigramRecommender
Dirichlet hyper-parameters of user-topic distribution: typical value is 50/K
initAlpha - Variable in class net.librec.recommender.cf.ranking.LDARecommender
Dirichlet hyper-parameters of user-topic distribution: typical value is 50/K
initBeta - Variable in class net.librec.recommender.cf.ranking.ItemBigramRecommender
Dirichlet hyper-parameters of topic-item distribution, typical value is 0.01
initBeta - Variable in class net.librec.recommender.cf.ranking.LDARecommender
Dirichlet hyper-parameters of topic-item distribution, typical value is 0.01
initMean - Variable in class net.librec.recommender.MatrixFactorizationRecommender
init mean
initModel() - Method in class net.librec.recommender.cf.rating.BPMFRecommender
Initialize the model
initSize(int) - Static method in class net.librec.util.Lists
 
initSize(Collection<E>) - Static method in class net.librec.util.Lists
 
initStd - Variable in class net.librec.recommender.MatrixFactorizationRecommender
init standard deviation
initTe() - Method in class net.librec.recommender.context.rating.TrustMFRecommender
 
initTr() - Method in class net.librec.recommender.context.rating.TrustMFRecommender
 
inner(DenseVector) - Method in class net.librec.math.structure.DenseVector
Do vector operation: a^t * b
inner(SparseVector) - Method in class net.librec.math.structure.DenseVector
Do vector operation: a^t * b
inner(SparseVector) - Method in class net.librec.math.structure.SparseVector
Return inner product with a given sparse vector
inner(DenseVector) - Method in class net.librec.math.structure.SparseVector
Return inner product with a given dense vector.
innerProduct(SparseTensor) - Method in class net.librec.math.structure.SparseTensor
 
intersect(List<T>, List<T>) - Static method in class net.librec.util.Lists
 
ints(int, int) - Static method in class net.librec.math.algorithm.Randoms
 
ints(int, int, int) - Static method in class net.librec.math.algorithm.Randoms
 
inv() - Method in class net.librec.math.structure.DenseMatrix
NOTE: this implementation (adopted from PREA package) is slightly faster than inverse, especially when numRows is large.
invDigamma(double) - Static method in class net.librec.math.algorithm.Gamma
Newton iteration to solve digamma(x)-y = 0.
inverse() - Method in class net.librec.math.structure.DenseMatrix
Deprecated.
use inv instead which is slightly faster
IOUtil - Class in net.librec.util
IOUtil
IOUtil() - Constructor for class net.librec.util.IOUtil
 
isBoldDriver - Variable in class net.librec.recommender.AbstractRecommender
whether to adjust learning rate automatically
isBoldDriver - Variable in class net.librec.recommender.TensorRecommender
whether to adjust learning rate automatically
isConverged(int) - Method in class net.librec.recommender.AbstractRecommender
Post each iteration, we do things: print debug information check if converged if not, adjust learning rate
isConverged(int) - Method in class net.librec.recommender.baseline.ItemClusterRecommender
 
isConverged(int) - Method in class net.librec.recommender.baseline.UserClusterRecommender
 
isConverged(int) - Method in class net.librec.recommender.cf.BUCMRecommender
 
isConverged(int) - Method in class net.librec.recommender.cf.ranking.SLIMRecommender
 
isConverged(int) - Method in class net.librec.recommender.cf.rating.LDCCRecommender
 
isConverged(int) - Method in class net.librec.recommender.cf.rating.URPRecommender
 
isConverged(int) - Method in class net.librec.recommender.MatrixFactorizationRecommender
Post each iteration, we do things: print debug information check if converged if not, adjust learning rate
isConverged(int) - Method in class net.librec.recommender.TensorRecommender
Post each iteration, we do things: print debug information check if converged if not, adjust learning rate
isCubical() - Method in class net.librec.math.structure.SparseTensor
 
isDiagonal() - Method in class net.librec.math.structure.SparseTensor
 
isDimMatch(SparseTensor) - Method in class net.librec.math.structure.SparseTensor
Return whether two sparse tensors have the same dimensions
isEmpty(List<T>) - Static method in class net.librec.util.Lists
 
isEqual(double, double) - Static method in class net.librec.math.algorithm.Maths
 
isIndexed(int) - Method in class net.librec.math.structure.SparseTensor
Return whether a dimension d is indexed.
isInt(double) - Static method in class net.librec.math.algorithm.Maths
 
isNumber(String) - Static method in class net.librec.math.algorithm.Maths
Check if given string is a number (digits only)
isNumberWith2Decimals(String) - Static method in class net.librec.math.algorithm.Maths
Check if given string is number with dot separator and two decimals.
isNumeric(String) - Static method in class net.librec.math.algorithm.Maths
Check if given string is numeric (-+0..9(.)0...9)
isOn(String) - Static method in class net.librec.util.StringUtil
 
isRanking - Variable in class net.librec.recommender.AbstractRecommender
is ranking or rating
isRanking - Variable in class net.librec.recommender.TensorRecommender
is ranking or rating
isShuffle - Variable in class net.librec.math.structure.SparseMatrix
 
ItemAverageRecommender - Class in net.librec.recommender.baseline
Baseline: predict by the average of target item's ratings
ItemAverageRecommender() - Constructor for class net.librec.recommender.baseline.ItemAverageRecommender
 
itemBiases - Variable in class net.librec.recommender.cf.rating.BiasedMFRecommender
user biases
ItemBigramRecommender - Class in net.librec.recommender.cf.ranking
Hanna M.
ItemBigramRecommender() - Constructor for class net.librec.recommender.cf.ranking.ItemBigramRecommender
 
ItemClusterRecommender - Class in net.librec.recommender.baseline
It is a graphical model that clusters items into K groups for recommendation, as opposite to the UserCluster recommender.
ItemClusterRecommender() - Constructor for class net.librec.recommender.baseline.ItemClusterRecommender
 
itemDimension - Variable in class net.librec.recommender.TensorRecommender
user and item index of tensor
ItemEntry<K,V> - Class in net.librec.recommender.item
Hashtable bucket collision list entry
ItemEntry(K, V) - Constructor for class net.librec.recommender.item.ItemEntry
 
itemFactors - Variable in class net.librec.recommender.MatrixFactorizationRecommender
item latent factors
itemFeatureMatrix - Variable in class net.librec.recommender.content.EFMRecommender
 
itemFeatureQuality - Variable in class net.librec.recommender.content.EFMRecommender
 
itemHiddenMatrix - Variable in class net.librec.recommender.content.EFMRecommender
 
ItemKNNRecommender - Class in net.librec.recommender.cf
ItemKNNRecommender
ItemKNNRecommender() - Constructor for class net.librec.recommender.cf.ItemKNNRecommender
 
itemMappingData - Variable in class net.librec.recommender.AbstractRecommender
item Mapping Data
itemMappingData - Variable in class net.librec.recommender.TensorRecommender
item Mapping Data
itemProbs - Variable in class net.librec.recommender.cf.ranking.RankSGDRecommender
 
itemUsersCache - Variable in class net.librec.recommender.cf.ranking.GBPRRecommender
user-items cache, item-users cache
iterator() - Method in class net.librec.conf.Configuration
Get an Iterator to go through the list of String key-value pairs in the configuration.
iterator() - Method in class net.librec.math.structure.SparseMatrix
 
iterator() - Method in class net.librec.math.structure.SparseTensor
 
iterator() - Method in class net.librec.math.structure.SparseVector
 

J

JaccardSimilarity - Class in net.librec.similarity
Jaccard Similarity
JaccardSimilarity() - Constructor for class net.librec.similarity.JaccardSimilarity
 
JDBCDataConvertor - Class in net.librec.data.convertor
JDBC Data Convertor
JDBCDataConvertor() - Constructor for class net.librec.data.convertor.JDBCDataConvertor
 
JDBCDataModel - Class in net.librec.data.model
JDBC Data Model
JDBCDataModel() - Constructor for class net.librec.data.model.JDBCDataModel
 
JobStatus - Class in net.librec.job
 
JobStatus() - Constructor for class net.librec.job.JobStatus
 
JobUtil - Class in net.librec.util
JobUtil
JobUtil() - Constructor for class net.librec.util.JobUtil
 

K

K - Variable in class net.librec.recommender.content.HFTRecommender
 
k - Variable in class net.librec.recommender.FactorizationMachineRecommender
number of factors
KCVDataSplitter - Class in net.librec.data.splitter
K-fold Cross Validation Data Splitter
KCVDataSplitter() - Constructor for class net.librec.data.splitter.KCVDataSplitter
Empty constructor.
KCVDataSplitter(DataConvertor, Configuration) - Constructor for class net.librec.data.splitter.KCVDataSplitter
Initializes a newly created KCVDataSplitter object with convertor and configuration.
kernelize(double, double, int) - Static method in class net.librec.math.algorithm.KernelSmoothing
 
KernelSmoothing - Class in net.librec.math.algorithm
This is a class implementing kernel smoothing functions used in Local Low-Rank Matrix Approximation (LLORMA).
KernelSmoothing() - Constructor for class net.librec.math.algorithm.KernelSmoothing
 
key(int, int) - Method in class net.librec.math.structure.SparseTensor
Return key in the position index of dimension d.
key(int) - Method in interface net.librec.math.structure.TensorEntry
 
keys(int) - Method in class net.librec.math.structure.SparseTensor
Return keys in a given index
keys() - Method in interface net.librec.math.structure.TensorEntry
 
khatriRaoProduct(DenseMatrix, DenseMatrix) - Static method in class net.librec.math.structure.DenseMatrix
Return Khatri-Rao product of two matrices.
knn - Static variable in class net.librec.recommender.cf.ranking.SLIMRecommender
number of nearest neighbors
KRCCSimilarity - Class in net.librec.similarity
J.
KRCCSimilarity() - Constructor for class net.librec.similarity.KRCCSimilarity
 
kroneckerProduct(DenseMatrix, DenseMatrix) - Static method in class net.librec.math.structure.DenseMatrix
Return Kronecker product of two arbitrary matrices
kroneckerProduct(DenseVector, DenseVector) - Static method in class net.librec.math.structure.DenseVector
Return the Kronecker product of two vectors

L

lambda - Variable in class net.librec.recommender.hybrid.HybridRecommender
 
lambdaH - Variable in class net.librec.recommender.content.EFMRecommender
 
lambdaU - Variable in class net.librec.recommender.content.EFMRecommender
 
lambdaV - Variable in class net.librec.recommender.content.EFMRecommender
 
lambdaX - Variable in class net.librec.recommender.content.EFMRecommender
 
lambdaY - Variable in class net.librec.recommender.content.EFMRecommender
 
last(String, int) - Static method in class net.librec.util.StringUtil
get the last substring of string str with maximum length
lastLoss - Variable in class net.librec.recommender.AbstractRecommender
objective loss
lastLoss - Variable in class net.librec.recommender.TensorRecommender
objective loss
lcm(int, int) - Static method in class net.librec.math.algorithm.Maths
least common multiple (lcm).
LDARecommender - Class in net.librec.recommender.cf.ranking
Latent Dirichlet Allocation for implicit feedback: Tom Griffiths, Gibbs sampling in the generative model of Latent Dirichlet Allocation, 2002.
LDARecommender() - Constructor for class net.librec.recommender.cf.ranking.LDARecommender
 
LDCCRecommender - Class in net.librec.recommender.cf.rating
 
LDCCRecommender() - Constructor for class net.librec.recommender.cf.rating.LDCCRecommender
 
learnRate - Variable in class net.librec.recommender.cf.rating.LLORMAUpdater
Learning rate parameter.
learnRate - Variable in class net.librec.recommender.cf.rating.RFRecRecommender
 
learnRate - Variable in class net.librec.recommender.MatrixFactorizationRecommender
learn rate, maximum learning rate
learnRate - Variable in class net.librec.recommender.TensorRecommender
learn rate, maximum learning rate
LibrecContext - Interface in net.librec.common
LibrecContext
LibrecException - Exception in net.librec.common
The class LibrecException and its subclasses are a form of Throwable that indicates conditions that a reasonable application might want to catch.
LibrecException() - Constructor for exception net.librec.common.LibrecException
Constructs a new exception with null as its detail message.
LibrecException(String, Throwable) - Constructor for exception net.librec.common.LibrecException
Constructs a new exception with the specified detail message and cause.
LibrecException(String) - Constructor for exception net.librec.common.LibrecException
Constructs a new exception with the specified detail message.
LibrecException(Throwable) - Constructor for exception net.librec.common.LibrecException
Constructs a new exception with the specified cause and a detail message of (cause==null ? null : cause.toString()) (which typically contains the class and detail message of cause).
LibrecTool - Interface in net.librec.tool
RecDriver
LibrecWaring - Annotation Type in net.librec.annotation
Librec Waring Annotation
LibSVMPreference - Class in net.librec.data.preference
Deprecated.
LibSVMPreference() - Constructor for class net.librec.data.preference.LibSVMPreference
Deprecated.
 
LINE_SEPARATOR - Static variable in class net.librec.util.IOUtil
The system line separator string.
LINE_SEPARATOR_UNIX - Static variable in class net.librec.util.IOUtil
The Unix line separator string.
LINE_SEPARATOR_WINDOWS - Static variable in class net.librec.util.IOUtil
The Windows line separator string.
list(int) - Static method in class net.librec.math.algorithm.Randoms
 
list(int, int, int) - Static method in class net.librec.math.algorithm.Randoms
 
list(int, int, int, boolean) - Static method in class net.librec.math.algorithm.Randoms
 
listFiles(String) - Static method in class net.librec.util.FileUtil
list all files of a given folder
Lists - Class in net.librec.util
This class is for the operations of arrays or collections
Lists() - Constructor for class net.librec.util.Lists
 
ListwiseMFRecommender - Class in net.librec.recommender.cf.ranking
Shi et al., List-wise learning to rank with matrix factorization for collaborative filtering, RecSys 2010.
ListwiseMFRecommender() - Constructor for class net.librec.recommender.cf.ranking.ListwiseMFRecommender
 
LLORMARecommender - Class in net.librec.recommender.cf.rating
Local Low-Rank Matrix Approximation
LLORMARecommender() - Constructor for class net.librec.recommender.cf.rating.LLORMARecommender
 
LLORMAUpdater - Class in net.librec.recommender.cf.rating
Local Low-Rank Matrix Approximation
LLORMAUpdater(int, int, int, int, int, int, double, double, double, int, DenseVector, DenseVector, SparseMatrix) - Constructor for class net.librec.recommender.cf.rating.LLORMAUpdater
Construct a local model for singleton LLORMA.
ln(double) - Static method in class net.librec.math.algorithm.Maths
Return ln(e)=log_e(n)
loadDataModel() - Method in interface net.librec.data.DataModel
Load data model.
loadDataModel() - Method in class net.librec.data.model.AbstractDataModel
Load data model.
loadDataModel() - Method in class net.librec.data.model.TextDataModel
Load data model.
loadModel(String) - Method in class net.librec.recommender.AbstractRecommender
(non-Javadoc)
loadModel(String) - Method in interface net.librec.recommender.Recommender
load Model
loadModel(String) - Method in class net.librec.recommender.TensorRecommender
 
localIteration - Variable in class net.librec.recommender.cf.rating.LLORMAUpdater
The maximum number of iteration.
localRegItem - Variable in class net.librec.recommender.cf.rating.LLORMARecommender
 
localRegItem - Variable in class net.librec.recommender.cf.rating.LLORMAUpdater
Regularization factor parameter.
localRegUser - Variable in class net.librec.recommender.cf.rating.LLORMARecommender
 
localRegUser - Variable in class net.librec.recommender.cf.rating.LLORMAUpdater
Regularization factor parameter.
LOG - Variable in class net.librec.data.model.AbstractDataModel
LOG
LOG - Variable in class net.librec.data.splitter.AbstractDataSplitter
LOG
LOG - Variable in class net.librec.job.RecommenderJob
LOG
log(double, int) - Static method in class net.librec.math.algorithm.Maths
 
LOG - Variable in class net.librec.recommender.AbstractRecommender
LOG
LOG - Variable in class net.librec.recommender.FactorizationMachineRecommender
LOG
LOG - Variable in class net.librec.recommender.TensorRecommender
LOG
logGamma(double) - Static method in class net.librec.math.algorithm.Gamma
log Gamma function: log(gamma(alpha)) for alpha bigger than 0, accurate to 10 decimal places
logistic(double) - Static method in class net.librec.math.algorithm.Maths
logistic function g(x)
logisticGradientValue(double) - Static method in class net.librec.math.algorithm.Maths
Gradient value of logistic function logistic(x).
logSum(double, double) - Static method in class net.librec.math.algorithm.Maths
Given log(a) and log(b), return log(a + b)
logValue - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrix
 
logValue - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrixGR
 
logValue - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseVector
 
LOOCVDataSplitter - Class in net.librec.data.splitter
Leave one out Splitter
Leave random or the last one user/item out as test set and the rest treated
as the train set.
LOOCVDataSplitter() - Constructor for class net.librec.data.splitter.LOOCVDataSplitter
Empty constructor.
LOOCVDataSplitter(DataConvertor, Configuration) - Constructor for class net.librec.data.splitter.LOOCVDataSplitter
Initializes a newly created LOOCVDataSplitter object with convertor and configuration.
loss - Variable in class net.librec.recommender.AbstractRecommender
objective loss
loss - Variable in class net.librec.recommender.TensorRecommender
objective loss

M

MAEEvaluator - Class in net.librec.eval.rating
MAE: mean absolute error
MAEEvaluator() - Constructor for class net.librec.eval.rating.MAEEvaluator
 
main(String[]) - Static method in class net.librec.math.algorithm.Gaussian
 
main(String[]) - Static method in class net.librec.math.structure.SparseTensor
Usage demonstration
main(String[]) - Static method in class net.librec.tool.driver.DataDriver
 
main(String[]) - Static method in class net.librec.tool.driver.RecDriver
 
makeDirectory(String) - Static method in class net.librec.util.FileUtil
Make directory if it does not exist
makeDirectory(String...) - Static method in class net.librec.util.FileUtil
Construct directory and return directory path
makeDirPath(String) - Static method in class net.librec.util.FileUtil
Make directory path: make sure the path is ended with file separator
makeDirPath(String...) - Static method in class net.librec.util.FileUtil
Make directory path using the names of directories.
Maths - Class in net.librec.math.algorithm
 
Maths() - Constructor for class net.librec.math.algorithm.Maths
 
matricization(int) - Method in class net.librec.math.structure.SparseTensor
Re-ordering entries of a tensor into a matrix
MatrixEntry - Interface in net.librec.math.structure
An entry of a matrix.
MatrixFactorizationRecommender - Class in net.librec.recommender
Matrix Factorization Recommender Methods with user factors and item factors: such as SVD(Singular Value Decomposition)
MatrixFactorizationRecommender() - Constructor for class net.librec.recommender.MatrixFactorizationRecommender
 
matString() - Method in class net.librec.math.structure.SparseMatrix
 
matString() - Method in class net.librec.math.structure.SparseStringMatrix
 
max(double[]) - Static method in class net.librec.math.algorithm.Stats
Find out the maximum element and its index of an array
max(int[]) - Static method in class net.librec.math.algorithm.Stats
Find out the maximum element and its index of an array.
maxLearnRate - Variable in class net.librec.recommender.MatrixFactorizationRecommender
learn rate, maximum learning rate
maxLearnRate - Variable in class net.librec.recommender.TensorRecommender
learn rate, maximum learning rate
maxRate - Variable in class net.librec.recommender.AbstractRecommender
Maximum rate of rating scale
maxRate - Variable in class net.librec.recommender.TensorRecommender
Maximum rate of rating scale
mean(Collection<? extends Number>) - Static method in class net.librec.math.algorithm.Maths
Return mean value of a sample.
mean(Collection<? extends Number>) - Static method in class net.librec.math.algorithm.Stats
Return mean value of a sample.
mean(double[]) - Static method in class net.librec.math.algorithm.Stats
reference: http://www.weibull.com/DOEWeb/unbiased_and_biased_estimators.htm
mean() - Method in class net.librec.math.structure.DenseVector
 
mean() - Method in class net.librec.math.structure.SparseMatrix
 
mean() - Method in class net.librec.math.structure.SparseTensor
 
mean() - Method in class net.librec.math.structure.SparseVector
 
Measure - Enum in net.librec.eval
Measure
Measure.MeasureValue - Class in net.librec.eval
 
MeasureValue(Measure) - Constructor for class net.librec.eval.Measure.MeasureValue
Construct with the measure type of the value.
MeasureValue(Measure, Integer) - Constructor for class net.librec.eval.Measure.MeasureValue
Construct with the measure type of the value and the number of items in the recommended list.
median(double[]) - Static method in class net.librec.math.algorithm.Stats
Calculate the median value of an array, Note that the values of doulbe.NaN will be ignored silently.
median(Collection<? extends Number>) - Static method in class net.librec.math.algorithm.Stats
Calculate the median value of a data collection, Note that the values of doulbe.NaN will be ignored silently
MFALSRecommender - Class in net.librec.recommender.cf.rating
The class implementing the Alternating Least Squares algorithm
MFALSRecommender() - Constructor for class net.librec.recommender.cf.rating.MFALSRecommender
 
min(int[]) - Static method in class net.librec.math.algorithm.Stats
Find out the minimum element and its index of an array.
min(double[]) - Static method in class net.librec.math.algorithm.Stats
Find out the minimum element and its index of an array.
minRate - Variable in class net.librec.recommender.AbstractRecommender
Minimum rate of rating scale
minRate - Variable in class net.librec.recommender.TensorRecommender
Minimum rate of rating scale
minus(DenseMatrix) - Method in class net.librec.math.structure.DenseMatrix
Do A - B matrix operation
minus(SparseMatrix) - Method in class net.librec.math.structure.DenseMatrix
Do A - B matrix operation
minus(double) - Method in class net.librec.math.structure.DenseMatrix
Do A - c matrix operation, where c is a constant.
minus(int, double) - Method in class net.librec.math.structure.DenseVector
Substract a value from entry [index]
minus(double) - Method in class net.librec.math.structure.DenseVector
Return a new dense vector by substructing a value from all entries of current vector a[i] = b[i] - c
minus(DenseVector) - Method in class net.librec.math.structure.DenseVector
Do vector operation: a - b
minus(DiagMatrix) - Method in class net.librec.math.structure.DiagMatrix
Do B - C diagonal matrix operation
minus(double) - Method in class net.librec.math.structure.DiagMatrix
Each diagonal entry abstracts val
minusEqual(DenseMatrix) - Method in class net.librec.math.structure.DenseMatrix
Do A - B matrix operation
minusEqual(SparseMatrix) - Method in class net.librec.math.structure.DenseMatrix
Do A - B matrix operation
minusEqual(double) - Method in class net.librec.math.structure.DenseMatrix
Do A - c matrix operation, where c is a constant.
minusEqual(double) - Method in class net.librec.math.structure.DenseVector
Return this dense vector by substructing a value from all entries of current vector b[i] = b[i] - c
minusEqual(DenseVector) - Method in class net.librec.math.structure.DenseVector
Do vector operation: a - b
minusEqual(DiagMatrix) - Method in class net.librec.math.structure.DiagMatrix
Do B - C diagonal matrix operation
minusEqual(double) - Method in class net.librec.math.structure.DiagMatrix
Each diagonal entry abstracts val
mode(double[]) - Static method in class net.librec.math.algorithm.Stats
 
model - Variable in class net.librec.recommender.context.rating.TrustMFRecommender
model selection identifier
ModelData - Annotation Type in net.librec.annotation
Data Model Annotation
modeProduct(DenseMatrix, int) - Method in class net.librec.math.structure.SparseTensor
n-mode product of a tensor A (I1 x I2 x ...
modeProduct(DenseVector, int) - Method in class net.librec.math.structure.SparseTensor
n-mode product of a tensor A (I1 x I2 x ...
MostPopularRecommender - Class in net.librec.recommender.baseline
Baseline: items are weighted by the number of ratings they received.
MostPopularRecommender() - Constructor for class net.librec.recommender.baseline.MostPopularRecommender
 
moveDirectory(String, String) - Static method in class net.librec.util.FileUtil
 
moveFile(String, String) - Static method in class net.librec.util.FileUtil
 
MPEEvaluator - Class in net.librec.eval.rating
MPE Evaluator
MPEEvaluator() - Constructor for class net.librec.eval.rating.MPEEvaluator
 
MSDSimilarity - Class in net.librec.similarity
Calculate Mean Squared Difference (MSD) similarity proposed by Shardanand and Maes [1995]: Social information filtering: Algorithms for automating "word of mouth"
MSDSimilarity() - Constructor for class net.librec.similarity.MSDSimilarity
 
MSEEvaluator - Class in net.librec.eval.rating
MSE: mean square error
MSEEvaluator() - Constructor for class net.librec.eval.rating.MSEEvaluator
 
MSESimilarity - Class in net.librec.similarity
Mean Square Error Similarity
MSESimilarity() - Constructor for class net.librec.similarity.MSESimilarity
 
mStep() - Method in class net.librec.recommender.baseline.ItemClusterRecommender
 
mStep() - Method in class net.librec.recommender.baseline.UserClusterRecommender
 
mStep() - Method in class net.librec.recommender.cf.BHFreeRecommender
 
mStep() - Method in class net.librec.recommender.cf.BUCMRecommender
Thomas P.
mStep() - Method in class net.librec.recommender.cf.ranking.AspectModelRecommender
 
mStep() - Method in class net.librec.recommender.cf.ranking.ItemBigramRecommender
 
mStep() - Method in class net.librec.recommender.cf.ranking.LDARecommender
 
mStep() - Method in class net.librec.recommender.cf.ranking.PLSARecommender
 
mStep() - Method in class net.librec.recommender.cf.rating.AspectModelRecommender
 
mStep() - Method in class net.librec.recommender.cf.rating.GPLSARecommender
 
mStep() - Method in class net.librec.recommender.cf.rating.LDCCRecommender
 
mStep() - Method in class net.librec.recommender.cf.rating.URPRecommender
Thomas P.
mStep() - Method in class net.librec.recommender.ProbabilisticGraphicalRecommender
update the hyper-parameters
mu - Variable in class net.librec.recommender.cf.rating.BPMFRecommender.HyperParameters
 
mult(DenseMatrix) - Method in class net.librec.math.structure.DenseMatrix
Matrix multiplication with a dense matrix
mult(SparseMatrix) - Method in class net.librec.math.structure.DenseMatrix
Matrix multiplication with a sparse matrix
mult(DenseVector) - Method in class net.librec.math.structure.DenseMatrix
Do matrix x vector between current matrix and a given vector
mult(SparseVector) - Method in class net.librec.math.structure.DenseMatrix
 
mult(SparseMatrix, DenseMatrix) - Static method in class net.librec.math.structure.DenseMatrix
Matrix multiplication of a sparse matrix by a dense matrix

N

n - Variable in class net.librec.recommender.FactorizationMachineRecommender
number of ratings
ndKeys - Variable in class net.librec.math.structure.SparseTensor
 
neiItemFactors - Variable in class net.librec.recommender.cf.rating.ASVDPlusPlusRecommender
 
net.librec.annotation - package net.librec.annotation
 
net.librec.common - package net.librec.common
 
net.librec.conf - package net.librec.conf
 
net.librec.data - package net.librec.data
 
net.librec.data.convertor - package net.librec.data.convertor
 
net.librec.data.convertor.appender - package net.librec.data.convertor.appender
 
net.librec.data.model - package net.librec.data.model
 
net.librec.data.preference - package net.librec.data.preference
 
net.librec.data.splitter - package net.librec.data.splitter
 
net.librec.eval - package net.librec.eval
 
net.librec.eval.ranking - package net.librec.eval.ranking
 
net.librec.eval.rating - package net.librec.eval.rating
 
net.librec.filter - package net.librec.filter
 
net.librec.job - package net.librec.job
 
net.librec.job.progress - package net.librec.job.progress
 
net.librec.math.algorithm - package net.librec.math.algorithm
 
net.librec.math.structure - package net.librec.math.structure
 
net.librec.recommender - package net.librec.recommender
 
net.librec.recommender.baseline - package net.librec.recommender.baseline
 
net.librec.recommender.cf - package net.librec.recommender.cf
 
net.librec.recommender.cf.ranking - package net.librec.recommender.cf.ranking
 
net.librec.recommender.cf.rating - package net.librec.recommender.cf.rating
 
net.librec.recommender.content - package net.librec.recommender.content
 
net.librec.recommender.context.ranking - package net.librec.recommender.context.ranking
 
net.librec.recommender.context.rating - package net.librec.recommender.context.rating
 
net.librec.recommender.ext - package net.librec.recommender.ext
 
net.librec.recommender.hybrid - package net.librec.recommender.hybrid
 
net.librec.recommender.item - package net.librec.recommender.item
 
net.librec.similarity - package net.librec.similarity
 
net.librec.tool - package net.librec.tool
 
net.librec.tool.driver - package net.librec.tool.driver
 
net.librec.util - package net.librec.util
 
newInstance(Class<T>, Class<?>, Object) - Static method in class net.librec.util.ReflectionUtil
Create an object for the given class and initialize it from conf
newInstance(Class<T>, Configuration) - Static method in class net.librec.util.ReflectionUtil
Create an object for the given class and initialize it from conf
newInstance(Class<T>) - Static method in class net.librec.util.ReflectionUtil
 
nextInt(int, int...) - Static method in class net.librec.math.algorithm.Randoms
generate next random integer in a range besides exceptions
nextInt(int, int, int...) - Static method in class net.librec.math.algorithm.Randoms
generate next random integer in a range [min, max) besides exceptions
nextIntArray(int, int) - Static method in class net.librec.math.algorithm.Randoms
generate next integers array with no repeated elements
nextIntArray(int, int, int...) - Static method in class net.librec.math.algorithm.Randoms
 
nextIntArray(int, int, int) - Static method in class net.librec.math.algorithm.Randoms
 
nextIntArray(int, int, int, int...) - Static method in class net.librec.math.algorithm.Randoms
 
NMFRecommender - Class in net.librec.recommender.cf.rating
Daniel D.
NMFRecommender() - Constructor for class net.librec.recommender.cf.rating.NMFRecommender
 
norm(double[]) - Static method in class net.librec.math.algorithm.Maths
 
norm() - Method in class net.librec.math.structure.DenseMatrix
 
norm() - Method in class net.librec.math.structure.SparseTensor
 
norm2() - Method in class net.librec.math.algorithm.SVD
Two norm
normalize(double, double, double) - Static method in class net.librec.math.algorithm.Maths
Get the normalized value using min-max normalizaiton.
normalize(double, double) - Method in class net.librec.math.structure.SparseMatrix
Normalize the matrix entries to (0, 1) by (x-min)/(max-min)
normalize(double) - Method in class net.librec.math.structure.SparseMatrix
Normalize the matrix entries to (0, 1) by (x/max)
normalize(double) - Method in class net.librec.recommender.context.rating.SocialMFRecommender
normalize a rating to the region (0, 1)
NormalizedDCGEvaluator - Class in net.librec.eval.ranking
NormalizedDCGEvaluator
NormalizedDCGEvaluator() - Constructor for class net.librec.eval.ranking.NormalizedDCGEvaluator
 
now() - Static method in class net.librec.util.DateUtil
 
numberOfFeatures - Variable in class net.librec.recommender.content.EFMRecommender
 
numberOfItems - Variable in class net.librec.recommender.content.EFMRecommender
 
numberOfItems - Variable in class net.librec.recommender.content.HFTRecommender
 
numberOfUsers - Variable in class net.librec.recommender.content.EFMRecommender
 
numberOfUsers - Variable in class net.librec.recommender.content.HFTRecommender
 
numberOfWords - Variable in class net.librec.recommender.content.HFTRecommender
 
numColumns - Variable in class net.librec.math.structure.DenseMatrix
dimension
numColumns() - Method in class net.librec.math.structure.DenseMatrix
 
numColumns - Variable in class net.librec.math.structure.SparseMatrix
 
numColumns() - Method in class net.librec.math.structure.SparseMatrix
 
numColumns - Variable in class net.librec.math.structure.SparseStringMatrix
 
numColumns() - Method in class net.librec.math.structure.SparseStringMatrix
 
numColumns - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrix
 
numColumns - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrixGR
 
numDimensions - Variable in class net.librec.math.structure.SparseTensor
number of dimensions, i.e., the order (or modes, ways) of a tensor
numDimensions() - Method in class net.librec.math.structure.SparseTensor
 
numDimensions - Variable in class net.librec.recommender.TensorRecommender
dimensions
numFactors - Variable in class net.librec.recommender.FactorizationMachineRecommender
the number of latent factors
numFactors - Variable in class net.librec.recommender.MatrixFactorizationRecommender
the number of latent factors;
numFactors - Variable in class net.librec.recommender.TensorRecommender
number of factors
numItems() - Method in class net.librec.data.convertor.TextDataConvertor
Return the number of items.
numItems - Variable in class net.librec.recommender.AbstractRecommender
the number of items
numItems - Variable in class net.librec.recommender.ProbabilisticGraphicalRecommender
the number of items
numItems - Variable in class net.librec.recommender.TensorRecommender
the number of items
numItemsRateByUser - Variable in class net.librec.recommender.cf.ranking.PLSARecommender
entry[u]: number of tokens rated by user u.
numIterations - Variable in class net.librec.recommender.cf.ranking.SLIMRecommender
the number of iterations
numIterations - Variable in class net.librec.recommender.FactorizationMachineRecommender
the number of iterations
numIterations - Variable in class net.librec.recommender.MatrixFactorizationRecommender
the number of iterations
numIterations - Variable in class net.librec.recommender.ProbabilisticGraphicalRecommender
the number of iterations
numIterations - Variable in class net.librec.recommender.TensorRecommender
the number of iterations
numRates - Variable in class net.librec.recommender.AbstractRecommender
the number of rates
numRatingLevels - Variable in class net.librec.recommender.cf.BUCMRecommender
 
numRatingLevels - Variable in class net.librec.recommender.cf.rating.URPRecommender
 
numRows - Variable in class net.librec.math.structure.DenseMatrix
dimension
numRows() - Method in class net.librec.math.structure.DenseMatrix
 
numRows - Variable in class net.librec.math.structure.SparseMatrix
 
numRows() - Method in class net.librec.math.structure.SparseMatrix
 
numRows - Variable in class net.librec.math.structure.SparseStringMatrix
 
numRows() - Method in class net.librec.math.structure.SparseStringMatrix
 
numRows - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrix
 
numRows - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrixGR
 
numStats - Variable in class net.librec.recommender.cf.ranking.LDARecommender
size of statistics
numStats - Variable in class net.librec.recommender.ProbabilisticGraphicalRecommender
size of statistics
numTopics - Variable in class net.librec.recommender.cf.BUCMRecommender
number of topics
numTopics - Variable in class net.librec.recommender.cf.ranking.AspectModelRecommender
number of topics
numTopics - Variable in class net.librec.recommender.cf.ranking.ItemBigramRecommender
number of topics
numTopics - Variable in class net.librec.recommender.cf.ranking.LDARecommender
number of topics
numTopics - Variable in class net.librec.recommender.cf.ranking.PLSARecommender
number of latent topics
numTopics - Variable in class net.librec.recommender.cf.rating.AspectModelRecommender
 
numTopics - Variable in class net.librec.recommender.cf.rating.GPLSARecommender
 
numTopics - Variable in class net.librec.recommender.cf.rating.URPRecommender
number of topics
numUsers() - Method in class net.librec.data.convertor.TextDataConvertor
Return the number of users.
numUsers - Variable in class net.librec.recommender.AbstractRecommender
the number of users
numUsers - Variable in class net.librec.recommender.ProbabilisticGraphicalRecommender
the number of users
numUsers - Variable in class net.librec.recommender.TensorRecommender
the number of users

O

ONE_G - Static variable in class net.librec.util.FileUtil
 
ONE_GB - Static variable in class net.librec.util.FileUtil
 
ONE_K - Static variable in class net.librec.util.FileUtil
 
ONE_KB - Static variable in class net.librec.util.FileUtil
 
ONE_M - Static variable in class net.librec.util.FileUtil
 
ONE_MB - Static variable in class net.librec.util.FileUtil
 
oneHotEncoding() - Method in class net.librec.data.convertor.ArffDataConvertor
oneHotFeatureMatrix - Variable in class net.librec.data.convertor.ArffDataConvertor
 
oneHotRatingVector - Variable in class net.librec.data.convertor.ArffDataConvertor
 
OPERATING_SYSTEM - Static variable in class net.librec.util.Systems
 
outer(DenseVector) - Method in class net.librec.math.structure.DenseVector
Do vector operation: a * b^t
overlapSize(List<T>, List<T>) - Static method in class net.librec.util.Lists
 

P

P - Variable in class net.librec.recommender.context.rating.TimeSVDRecommender
factorized user-factor matrix
p - Variable in class net.librec.recommender.FactorizationMachineRecommender
appender vector size: number of users + number of items + number of contextual conditions
pareto(double) - Static method in class net.librec.math.algorithm.Randoms
Return a real number with a Pareto distribution with parameter alpha.
parse(String) - Static method in class net.librec.util.DateUtil
Parse the string of data into java.sql.Date object
parse(String, String) - Static method in class net.librec.util.DateUtil
Parse the string of data into java.sql.Date object with specified pattern
parse(long) - Static method in class net.librec.util.DateUtil
Convert time in milliseconds to human-readable format.
PATTERN_dd_MM_yyyy - Static variable in class net.librec.util.DateUtil
pattern
PATTERN_MM_dd_yyyy - Static variable in class net.librec.util.DateUtil
pattern
PATTERN_yyyy_MM_dd - Static variable in class net.librec.util.DateUtil
pattern
PATTERN_yyyy_MM_dd_HH_mm_SS - Static variable in class net.librec.util.DateUtil
pattern
pause() - Static method in class net.librec.util.Systems
Pause the system.
PCCSimilarity - Class in net.librec.similarity
Pearson Correlation Coefficient (PCC)
PCCSimilarity() - Constructor for class net.librec.similarity.PCCSimilarity
 
pdf(double) - Static method in class net.librec.math.algorithm.Gaussian
Standard Gaussian pdf.
pdf(double, double, double) - Static method in class net.librec.math.algorithm.Gaussian
Gaussian pdf with mean mu and stddev sigma
permute(int, int) - Static method in class net.librec.math.algorithm.Randoms
Generate a permutation from min to max
perplexity(int, int, double) - Method in class net.librec.recommender.cf.BUCMRecommender
 
perplexity(int, int, double) - Method in class net.librec.recommender.cf.rating.LDCCRecommender
 
PersonalityDiagnosisRecommender - Class in net.librec.recommender.ext
PersonalityDiagnosisRecommender() - Constructor for class net.librec.recommender.ext.PersonalityDiagnosisRecommender
 
phi(int) - Method in class net.librec.recommender.content.HFTRecommender
 
PhiInverse(double) - Static method in class net.librec.math.algorithm.Gaussian
Compute z for standard normal such that cdf(z) = y via bisection search
PhiInverse(double, double, double) - Static method in class net.librec.math.algorithm.Gaussian
Compute z for standard normal such that cdf(z, mu, sigma) = y via bisection search
phiks - Variable in class net.librec.recommender.content.HFTRecommender
 
pinv() - Method in class net.librec.math.structure.DenseMatrix
 
PLSARecommender - Class in net.librec.recommender.cf.ranking
Thomas Hofmann, Latent semantic models for collaborative filtering, ACM Transactions on Information Systems.
PLSARecommender() - Constructor for class net.librec.recommender.cf.ranking.PLSARecommender
 
PMFRecommender - Class in net.librec.recommender.cf.rating
PMF: Ruslan Salakhutdinov and Andriy Mnih, Probabilistic Matrix Factorization, NIPS 2008. RegSVD: Arkadiusz Paterek, Improving Regularized Singular Value Decomposition Collaborative Filtering, Proceedings of KDD Cup and Workshop, 2007.
PMFRecommender() - Constructor for class net.librec.recommender.cf.rating.PMFRecommender
 
poisson(double) - Static method in class net.librec.math.algorithm.Randoms
Return an integer with a Poisson distribution with mean lambda.
PRankDRecommender - Class in net.librec.recommender.ext
Neil Hurley, Personalised ranking with diversity, RecSys 2013.
PRankDRecommender() - Constructor for class net.librec.recommender.ext.PRankDRecommender
 
PrecisionEvaluator - Class in net.librec.eval.ranking
PrecisionEvaluator, calculate precision@n
PrecisionEvaluator() - Constructor for class net.librec.eval.ranking.PrecisionEvaluator
 
predict(int, int) - Method in class net.librec.recommender.AbstractRecommender
predict a specific rating for user userIdx on item itemIdx, note that the prediction is not bounded.
predict(int, int, boolean) - Method in class net.librec.recommender.AbstractRecommender
predict a specific rating for user userIdx on item itemIdx.
predict(int, int) - Method in class net.librec.recommender.baseline.ConstantGuessRecommender
constant value as the predictive rating for user userIdx on item itemIdx.
predict(int, int) - Method in class net.librec.recommender.baseline.GlobalAverageRecommender
the global average value as the predictive rating for user userIdx on item itemIdx.
predict(int, int) - Method in class net.librec.recommender.baseline.ItemAverageRecommender
the item ratings average value as the predictive rating for user userIdx on item itemIdx.
predict(int, int) - Method in class net.librec.recommender.baseline.ItemClusterRecommender
 
predict(int, int) - Method in class net.librec.recommender.baseline.MostPopularRecommender
The rated count as the predictive ranking score for user userIdx on item itemIdx.
predict(int, int) - Method in class net.librec.recommender.baseline.RandomGuessRecommender
a random value as the predictive rating for user userIdx on item itemIdx.
predict(int, int) - Method in class net.librec.recommender.baseline.UserAverageRecommender
the user ratings average value as the predictive rating for user userIdx on item itemIdx.
predict(int, int) - Method in class net.librec.recommender.baseline.UserClusterRecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.BHFreeRecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.BUCMRecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.ItemKNNRecommender
(non-Javadoc)
predict(int, int) - Method in class net.librec.recommender.cf.ranking.AspectModelRecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.ranking.FISMaucRecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.ranking.FISMrmseRecommender
 
predict(int, int, Set<Integer>) - Method in class net.librec.recommender.cf.ranking.GBPRRecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.ranking.ItemBigramRecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.ranking.LDARecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.ranking.PLSARecommender
 
predict(int, int, int) - Method in class net.librec.recommender.cf.ranking.SLIMRecommender
predict a specific ranking score for user userIdx on item itemIdx.
predict(int, int) - Method in class net.librec.recommender.cf.ranking.SLIMRecommender
predict a specific ranking score for user userIdx on item itemIdx.
predict(int, int) - Method in class net.librec.recommender.cf.ranking.WBPRRecommender
predict a specific rating for user userIdx on item itemIdx.
predict(int, int) - Method in class net.librec.recommender.cf.rating.AspectModelRecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.rating.ASVDPlusPlusRecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.rating.BiasedMFRecommender
predict a specific rating for user userIdx on item itemIdx.
predict(int, int) - Method in class net.librec.recommender.cf.rating.BPMFRecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.rating.BPoissMFRecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.rating.FMALSRecommender
Deprecated.
predict(int, int) - Method in class net.librec.recommender.cf.rating.FMSGDRecommender
Deprecated.
predict(int, int) - Method in class net.librec.recommender.cf.rating.GPLSARecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.rating.LDCCRecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.rating.LLORMARecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.rating.LLORMAUpdater
 
predict(int, int) - Method in class net.librec.recommender.cf.rating.NMFRecommender
predict a specific rating for user userIdx on item itemIdx.
predict(int, int) - Method in class net.librec.recommender.cf.rating.RBMRecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.rating.RFRecRecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.rating.SVDPlusPlusRecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.rating.URPRecommender
 
predict(int, int) - Method in class net.librec.recommender.cf.UserKNNRecommender
(non-Javadoc)
predict(int, int) - Method in class net.librec.recommender.content.EFMRecommender
 
predict(int, int) - Method in class net.librec.recommender.content.HFTRecommender
 
predict(int, int) - Method in class net.librec.recommender.context.ranking.SBPRRecommender
predict a specific ranking score for user userIdx on item itemIdx.
predict(int, int) - Method in class net.librec.recommender.context.rating.RSTERecommender
 
predict(int, int) - Method in class net.librec.recommender.context.rating.TimeSVDRecommender
predict a specific rating for user userIdx on item itemIdx.
predict(int, int) - Method in class net.librec.recommender.context.rating.TrustMFRecommender
 
predict(int, int) - Method in class net.librec.recommender.context.rating.TrustSVDRecommender
predict a specific rating for user userIdx on item itemIdx.
predict(int, int, boolean) - Method in class net.librec.recommender.context.rating.TrustSVDRecommender
 
predict(int, int) - Method in class net.librec.recommender.ext.AssociationRuleRecommender
predict a specific rating for user userIdx on item itemIdx.
predict(int, int) - Method in class net.librec.recommender.ext.ExternalRecommender
predict a specific rating for user userIdx on item itemIdx.
predict(int, int) - Method in class net.librec.recommender.ext.PersonalityDiagnosisRecommender
predict a specific rating for user userIdx on item itemIdx.
predict(int, int) - Method in class net.librec.recommender.ext.SlopeOneRecommender
predict a specific rating for user userIdx on item itemIdx.
predict(SparseVector) - Method in class net.librec.recommender.FactorizationMachineRecommender
Predict the rating given a sparse appender vector.
predict(SparseVector, boolean) - Method in class net.librec.recommender.FactorizationMachineRecommender
Predict the rating given a sparse appender vector.
predict(int, int) - Method in class net.librec.recommender.hybrid.HybridRecommender
 
predict(int, int) - Method in class net.librec.recommender.MatrixFactorizationRecommender
predict a specific rating for user userIdx on item itemIdx.
predict(int, int, boolean) - Method in class net.librec.recommender.SocialRecommender
 
predict(int[]) - Method in class net.librec.recommender.TensorRecommender
predict a specific rating for user userIdx on item itemIdx with some other contexts indices, note that the prediction is not bounded.
predict(int[], boolean) - Method in class net.librec.recommender.TensorRecommender
predict a specific rating for user userIdx on item itemIdx with some other contexts indices.
predictRanking(int, int) - Method in class net.librec.recommender.cf.BHFreeRecommender
 
predictRanking(int, int) - Method in class net.librec.recommender.cf.BUCMRecommender
 
predictRating(int, int) - Method in class net.librec.recommender.cf.BHFreeRecommender
 
predictRating(int, int) - Method in class net.librec.recommender.cf.BUCMRecommender
 
Preference - Interface in net.librec.data.preference
Deprecated.
PreferenceArray - Interface in net.librec.data.preference
Deprecated.
preferenceMatrix - Variable in class net.librec.data.convertor.AbstractDataConvertor
store rate data as {user, item, rate} matrix
preferenceMatrix - Variable in class net.librec.recommender.cf.ranking.WRMFRecommender
preferenceMatrix_{ui} = 1 if r_{ui}>0 or preferenceMatrix_{ui} = 0
PREP - Static variable in class net.librec.job.JobStatus
 
ProbabilisticGraphicalRecommender - Class in net.librec.recommender
Created by Keqiang Wang
ProbabilisticGraphicalRecommender() - Constructor for class net.librec.recommender.ProbabilisticGraphicalRecommender
 
processData() - Method in class net.librec.data.convertor.appender.DocumentDataAppender
Process appender data.
processData() - Method in class net.librec.data.convertor.appender.SocialDataAppender
Process appender data.
processData() - Method in class net.librec.data.convertor.ArffDataConvertor
Process the input data.
processData() - Method in class net.librec.data.convertor.TextDataConvertor
Process the input data.
processData() - Method in interface net.librec.data.DataAppender
Process appender data.
processData() - Method in interface net.librec.data.DataConvertor
Process the input data.
processEntry(K, V) - Method in interface net.librec.util.FileUtil.MapWriter
 
product(DenseMatrix, int, DenseMatrix, int) - Static method in class net.librec.math.structure.DenseMatrix
Dot product of row x col between two matrices.
progress() - Method in class net.librec.data.convertor.ArffDataConvertor
 
progress() - Method in class net.librec.data.convertor.TextDataConvertor
Set the progress for job status.
progress() - Method in interface net.librec.job.progress.Progressable
Report progress to the Librec framework.
PROGRESS_INTERVAL - Static variable in class net.librec.job.progress.ProgressReporter
 
Progressable - Interface in net.librec.job.progress
Progressable
ProgressReporter - Class in net.librec.job.progress
Progress Reporter
ProgressReporter() - Constructor for class net.librec.job.progress.ProgressReporter
 
progressx() - Method in class net.librec.job.progress.ProgressReporter
progress

Q

Q - Variable in class net.librec.recommender.cf.ranking.PLSARecommender
{user, item, {topic z, probability}}
Q - Variable in class net.librec.recommender.cf.rating.AspectModelRecommender
 
Q - Variable in class net.librec.recommender.cf.rating.GPLSARecommender
 
Q - Variable in class net.librec.recommender.context.rating.TimeSVDRecommender
factorized item-factor matrix
Q - Variable in class net.librec.recommender.FactorizationMachineRecommender
parameter matrix

R

randInts(int, int, int) - Static method in class net.librec.math.algorithm.Randoms
Generate a set of random (unique) integers in the range [min, max) with length length
random() - Static method in class net.librec.math.algorithm.Randoms
Return real number uniformly in [0, 1).
random(List<T>) - Static method in class net.librec.math.algorithm.Randoms
Return a random number from a given list of numbers.
RandomGuessRecommender - Class in net.librec.recommender.baseline
Baseline: predict by a random value in (minRate, maxRate)
RandomGuessRecommender() - Constructor for class net.librec.recommender.baseline.RandomGuessRecommender
 
Randoms - Class in net.librec.math.algorithm
 
Randoms() - Constructor for class net.librec.math.algorithm.Randoms
 
randProbs(int) - Static method in class net.librec.math.algorithm.Randoms
Get a normalize array of probabilities
rank() - Method in class net.librec.math.algorithm.SVD
Effective numerical matrix rank
RankALSRecommender - Class in net.librec.recommender.cf.ranking
Takacs and Tikk, Alternating Least Squares for Personalized Ranking , RecSys 2012.
RankALSRecommender() - Constructor for class net.librec.recommender.cf.ranking.RankALSRecommender
 
RankSGDRecommender - Class in net.librec.recommender.cf.ranking
Jahrer and Toscher, Collaborative Filtering Ensemble for Ranking, JMLR, 2012 (KDD Cup 2011 Track 2).
RankSGDRecommender() - Constructor for class net.librec.recommender.cf.ranking.RankSGDRecommender
 
rate - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrix
 
rate - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrixGR
 
rate - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseVector
 
rateMatrix() - Method in class net.librec.math.structure.SparseTensor
retrieve a rating matrix from the tensor.
ratePrior - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrix
 
ratePrior - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrixGR
 
ratePrior - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseVector
 
rating - Variable in class net.librec.recommender.content.EFMRecommender
 
RatingContext - Class in net.librec.util
 
RatingContext(int, int, long) - Constructor for class net.librec.util.RatingContext
Create a new object with the given rating time stamp, user index and item index.
ratingScale - Static variable in class net.librec.recommender.AbstractRecommender
a list of rating scales
RatioDataSplitter - Class in net.librec.data.splitter
Ratio Data Splitter.
Split dataset into train set, test set, valid set by ratio.
RatioDataSplitter() - Constructor for class net.librec.data.splitter.RatioDataSplitter
Empty constructor.
RatioDataSplitter(DataConvertor, Configuration) - Constructor for class net.librec.data.splitter.RatioDataSplitter
Initializes a newly created RatioDataSplitter object with convertor and configuration.
RBMRecommender - Class in net.librec.recommender.cf.rating
This class implementing user-oriented Restricted Boltzmann Machines for Collaborative Filtering
RBMRecommender() - Constructor for class net.librec.recommender.cf.rating.RBMRecommender
 
read(String) - Static method in class net.librec.util.URLReader
Read from the given url
read(String, String, int) - Static method in class net.librec.util.URLReader
Read from the given url, with specified proxyHost and proxyPort
read(String, Proxy) - Static method in class net.librec.util.URLReader
Read from the given url, with specified proxy.
readAsIDMap(String) - Static method in class net.librec.util.FileUtil
read a map in the form of Map<String, Double>.
readAsIDMap(String, String) - Static method in class net.librec.util.FileUtil
read a map in the form of Map<String, Double>
readAsList(String) - Static method in class net.librec.util.FileUtil
Read the content of a file and return it as a List<String>
readAsList(String, FileUtil.Converter<String, T>) - Static method in class net.librec.util.FileUtil
 
readAsMap(String) - Static method in class net.librec.util.FileUtil
 
readAsMap(String, String) - Static method in class net.librec.util.FileUtil
 
readAsMap(String, FileUtil.Converter<String, Object[]>) - Static method in class net.librec.util.FileUtil
 
readAsSet(String) - Static method in class net.librec.util.FileUtil
 
readAsSet(String, FileUtil.Converter<String, T>) - Static method in class net.librec.util.FileUtil
 
readAsString(String, String...) - Static method in class net.librec.util.FileUtil
Read the content of a file, if keywords are specified, then only lines with these keywords will be read
readAsString(String, int...) - Static method in class net.librec.util.FileUtil
Read String from file at specified line numbers, e.g.
readAsString(String) - Static method in class net.librec.util.FileUtil
 
readData() - Method in class net.librec.data.convertor.ArffDataConvertor
Read data from the data file.
readLines(InputStream) - Static method in class net.librec.util.IOUtil
Get the contents of an InputStream as a list of Strings, one entry per line, using the default character encoding of the platform.
readLines(InputStream, String) - Static method in class net.librec.util.IOUtil
Get the contents of an InputStream as a list of Strings, one entry per line, using the specified character encoding.
readLines(Reader) - Static method in class net.librec.util.IOUtil
Get the contents of a Reader as a list of Strings, one entry per line.
readoutParams() - Method in class net.librec.recommender.cf.BHFreeRecommender
 
readoutParams() - Method in class net.librec.recommender.cf.BUCMRecommender
 
readoutParams() - Method in class net.librec.recommender.cf.ranking.ItemBigramRecommender
 
readoutParams() - Method in class net.librec.recommender.cf.ranking.LDARecommender
Add to the statistics the values of theta and phi for the current state.
readoutParams() - Method in class net.librec.recommender.cf.rating.AspectModelRecommender
 
readoutParams() - Method in class net.librec.recommender.cf.rating.LDCCRecommender
 
readoutParams() - Method in class net.librec.recommender.cf.rating.URPRecommender
 
readoutParams() - Method in class net.librec.recommender.ProbabilisticGraphicalRecommender
read out parameters for each iteration
RecallEvaluator - Class in net.librec.eval.ranking
RecallEvaluator, calculate recall@n
RecallEvaluator() - Constructor for class net.librec.eval.ranking.RecallEvaluator
 
RecDriver - Class in net.librec.tool.driver
RecDriver
RecDriver() - Constructor for class net.librec.tool.driver.RecDriver
 
ReciprocalRankEvaluator - Class in net.librec.eval.ranking
ReciprocalRankEvaluator
ReciprocalRankEvaluator() - Constructor for class net.librec.eval.ranking.ReciprocalRankEvaluator
 
recommend(RecommenderContext) - Method in class net.librec.recommender.AbstractRecommender
recommend
recommend() - Method in class net.librec.recommender.AbstractRecommender
recommend * predict the ranking scores or ratings in the test data
recommend(RecommenderContext) - Method in interface net.librec.recommender.Recommender
recommend
recommend(RecommenderContext) - Method in class net.librec.recommender.TensorRecommender
recommend
recommend() - Method in class net.librec.recommender.TensorRecommender
recommend * predict the ranking scores or ratings in the test data
RecommendedFilter - Interface in net.librec.filter
Recommended Filter
RecommendedItem - Interface in net.librec.recommender.item
Recommended Item
RecommendedItemList - Class in net.librec.recommender.item
Recommended Item List
RecommendedItemList(int) - Constructor for class net.librec.recommender.item.RecommendedItemList
Constructs an empty list with the specified initial capacity(number of users).
RecommendedItemList(int, int) - Constructor for class net.librec.recommender.item.RecommendedItemList
Constructs an empty list with the specified initial capacity(number of users).
recommendedList - Variable in class net.librec.recommender.AbstractRecommender
Recommended Item List
RecommendedList - Interface in net.librec.recommender.item
Recommended List
recommendedList - Variable in class net.librec.recommender.TensorRecommender
Recommended Item List
Recommender - Interface in net.librec.recommender
General recommenders
RecommenderContext - Class in net.librec.recommender
RecommenderContext
RecommenderContext(Configuration) - Constructor for class net.librec.recommender.RecommenderContext
 
RecommenderContext(Configuration, DataModel) - Constructor for class net.librec.recommender.RecommenderContext
 
RecommenderContext(Configuration, DataModel, RecommenderSimilarity) - Constructor for class net.librec.recommender.RecommenderContext
 
RecommenderEvaluator - Interface in net.librec.eval
Implementations of this interface evaluate the quality of a Recommender's recommendations.
RecommenderJob - Class in net.librec.job
RecommenderJob
RecommenderJob(Configuration) - Constructor for class net.librec.job.RecommenderJob
 
RecommenderSimilarity - Interface in net.librec.similarity
Recommender Similarity
recommendRank() - Method in class net.librec.recommender.AbstractRecommender
recommend * predict the ranking scores in the test data
recommendRank() - Method in class net.librec.recommender.TensorRecommender
recommend * predict the ranking scores in the test data
recommendRating() - Method in class net.librec.recommender.AbstractRecommender
recommend * predict the ratings in the test data
recommendRating() - Method in class net.librec.recommender.FactorizationMachineRecommender
recommend * predict the ratings in the test data
recommendRating() - Method in class net.librec.recommender.TensorRecommender
recommend * predict the ratings in the test data
ReflectionUtil - Class in net.librec.util
 
ReflectionUtil() - Constructor for class net.librec.util.ReflectionUtil
 
reg - Variable in class net.librec.recommender.TensorRecommender
regularization of user, item and all context
regBias - Variable in class net.librec.recommender.cf.ranking.GBPRRecommender
bias regularization
regBias - Variable in class net.librec.recommender.cf.ranking.WBPRRecommender
bias regularization
regBias - Variable in class net.librec.recommender.cf.rating.BiasedMFRecommender
bias regularization
regBias - Variable in class net.librec.recommender.context.ranking.SBPRRecommender
bias regularization
regBias - Variable in class net.librec.recommender.context.rating.TrustSVDRecommender
bias regularization
regF - Variable in class net.librec.recommender.FactorizationMachineRecommender
regularization term for weight and factors
regItem - Variable in class net.librec.recommender.MatrixFactorizationRecommender
item regularization
regSocial - Variable in class net.librec.recommender.SocialRecommender
social regularization
regUser - Variable in class net.librec.recommender.MatrixFactorizationRecommender
user regularization
regW - Variable in class net.librec.recommender.FactorizationMachineRecommender
regularization term for weight and factors
regW0 - Variable in class net.librec.recommender.FactorizationMachineRecommender
regularization term for weight and factors
remove(int...) - Method in class net.librec.math.structure.SparseTensor
remove an entry with specific keys.
remove() - Method in interface net.librec.math.structure.TensorEntry
remove current entry
removeUserIdx(int) - Method in class net.librec.recommender.item.RecommendedItemList
Removes the element at the specified position in this list.
removeUserIdx(int) - Method in interface net.librec.recommender.item.RecommendedList
remove UserIdx
renameFile(File, String, String) - Static method in class net.librec.util.FileUtil
 
renameFiles(String, String, String) - Static method in class net.librec.util.FileUtil
Rename files in a folder by replacing keywords
repeat(char, int) - Static method in class net.librec.util.StringUtil
Returns padding using the specified delimiter repeated to a given length.
repeat(String, int) - Static method in class net.librec.util.StringUtil
Repeat a String repeat times to form a new String.
reshape(SparseMatrix) - Static method in class net.librec.math.structure.SparseMatrix
remove zero entries of the given matrix
reshape(int, int) - Method in class net.librec.math.structure.SparseMatrix
Return a new matrix with shape (rows, cols) with data from the current matrix.
Resource(Object) - Constructor for class net.librec.conf.Configuration.Resource
 
Resource(Object, String) - Constructor for class net.librec.conf.Configuration.Resource
 
reviewMatrix - Variable in class net.librec.recommender.content.HFTRecommender
 
RFRecRecommender - Class in net.librec.recommender.cf.rating
Gedikli et al., RF-Rec: Fast and Accurate Computation of Recommendations based on Rating Frequencies, IEEE (CEC) 2011, Luxembourg, 2011, pp.
RFRecRecommender() - Constructor for class net.librec.recommender.cf.rating.RFRecRecommender
 
RMSEEvaluator - Class in net.librec.eval.rating
RMSE: root mean square error
RMSEEvaluator() - Constructor for class net.librec.eval.rating.RMSEEvaluator
 
rn - Variable in class net.librec.recommender.content.HFTRecommender
 
row(int) - Method in class net.librec.math.structure.DenseMatrix
Return a copy of row data as a dense vector.
row(int, boolean) - Method in class net.librec.math.structure.DenseMatrix
Return a vector of a specific row.
row() - Method in interface net.librec.math.structure.MatrixEntry
Returns the current row index
row(int) - Method in class net.librec.math.structure.SparseMatrix
get a row sparse vector of a matrix
row(int, int) - Method in class net.librec.math.structure.SparseMatrix
get a row sparse vector of a matrix
row(int) - Method in class net.librec.math.structure.SymmMatrix
Retrieve a complete row of similar items
rowCache(String) - Method in class net.librec.math.structure.SparseMatrix
create a row cache of a matrix in {row, row-specific vector}
rowColumnsCache(String) - Method in class net.librec.math.structure.SparseMatrix
create a row cache of a matrix in {row, row-specific columns}
rowColumnsSetCache(String) - Method in class net.librec.math.structure.SparseMatrix
create a row cache of a matrix in {row, row-specific columns}
rowData - Variable in class net.librec.math.structure.SparseMatrix
 
rowData - Variable in class net.librec.math.structure.SparseStringMatrix
 
rowInd - Variable in class net.librec.math.structure.SparseMatrix
 
rowInd - Variable in class net.librec.math.structure.SparseStringMatrix
 
rowIterator(int) - Method in class net.librec.math.structure.SparseMatrix
 
rowMult(DenseMatrix, int, DenseMatrix, int) - Static method in class net.librec.math.structure.DenseMatrix
Inner product of two row vectors
rowPtr - Variable in class net.librec.math.structure.SparseMatrix
 
rowPtr - Variable in class net.librec.math.structure.SparseStringMatrix
 
rows() - Method in class net.librec.math.structure.SparseMatrix
 
rows() - Method in class net.librec.math.structure.SparseStringMatrix
 
rowSize(int) - Method in class net.librec.math.structure.SparseMatrix
query the size of a specific row
rowSize(int) - Method in class net.librec.math.structure.SparseStringMatrix
query the size of a specific row
RSTERecommender - Class in net.librec.recommender.context.rating
Hao Ma, Irwin King and Michael R.
RSTERecommender() - Constructor for class net.librec.recommender.context.rating.RSTERecommender
 
run() - Method in class net.librec.job.progress.ProgressReporter
 
run() - Method in class net.librec.recommender.cf.rating.LLORMAUpdater
Learn this local model based on similar users to the anchor user and similar items to the anchor item.
run(String[]) - Method in class net.librec.tool.driver.DataDriver
Execute the command with the given arguments.
run(String[]) - Method in class net.librec.tool.driver.RecDriver
Execute the command with the given arguments.
run(String[]) - Method in interface net.librec.tool.LibrecTool
Execute the command with the given arguments.
runJob() - Method in class net.librec.job.RecommenderJob
run Job
RUNNING - Static variable in class net.librec.job.JobStatus
 

S

sampleLag - Variable in class net.librec.recommender.ProbabilisticGraphicalRecommender
sample lag (if -1 only one sample taken)
sampleZ() - Method in class net.librec.recommender.content.HFTRecommender
 
samplingHyperParameters(BPMFRecommender.HyperParameters, DenseMatrix, DenseVector, double, DenseMatrix, double) - Method in class net.librec.recommender.cf.rating.BPMFRecommender
 
saveDataModel() - Method in interface net.librec.data.DataModel
Save data model.
saveDataModel() - Method in class net.librec.data.model.AbstractDataModel
Save data model.
saveDataModel() - Method in class net.librec.data.model.TextDataModel
Save data model.
saveModel(String) - Method in class net.librec.recommender.AbstractRecommender
(non-Javadoc)
saveModel(String) - Method in interface net.librec.recommender.Recommender
save Model
saveModel(String) - Method in class net.librec.recommender.TensorRecommender
 
saveResult(List<RecommendedItem>) - Method in class net.librec.job.RecommenderJob
Save result.
SBPRRecommender - Class in net.librec.recommender.context.ranking
Social Bayesian Personalized Ranking (SBPR)
SBPRRecommender() - Constructor for class net.librec.recommender.context.ranking.SBPRRecommender
 
scale(double) - Method in class net.librec.math.structure.DenseMatrix
Return a new matrix by scaling the current matrix.
scale(double) - Method in class net.librec.math.structure.DenseVector
Return a new dense vector by scaling a value to all entries of current vector a = b.scale(c)
scale(double) - Method in class net.librec.math.structure.DiagMatrix
Return a new diagonal matrix by scaling the current diagonal matrix.
scaleEqual(double) - Method in class net.librec.math.structure.DenseMatrix
Return this matrix by scaling the current matrix.
scaleEqual(double) - Method in class net.librec.math.structure.DenseVector
Return this dense vector by scaling a value to all entries of current vector b = b.scale(c).
scaleEqual(double) - Method in class net.librec.math.structure.DiagMatrix
Return this diagonal matrix by scaling the current diagonal matrix.
scoreScale - Variable in class net.librec.recommender.content.EFMRecommender
 
sd(Collection<? extends Number>) - Static method in class net.librec.math.algorithm.Stats
Calculate the standard deviation.
sd(Collection<? extends Number>, double) - Static method in class net.librec.math.algorithm.Stats
Calculate the standard deviation.
sd(double[]) - Static method in class net.librec.math.algorithm.Stats
Calculate a sample's standard deviation.
sd(double[], double) - Static method in class net.librec.math.algorithm.Stats
Calculate a sample's standard deviation.
seed(long) - Static method in class net.librec.math.algorithm.Randoms
 
serialize(Object, String) - Static method in class net.librec.util.FileUtil
 
set(String, String) - Method in class net.librec.conf.Configuration
Set the value of the name property.
set(int, int, double) - Method in interface net.librec.math.structure.DataMatrix
Set a value to entry [row, column]
set(int, int, double) - Method in class net.librec.math.structure.DenseMatrix
Set a value to entry [row, column]
set(int, double) - Method in class net.librec.math.structure.DenseVector
Set a value to entry [index]
set(double) - Method in interface net.librec.math.structure.MatrixEntry
Sets the value at the current index
set(int, int, double) - Method in class net.librec.math.structure.SparseMatrix
Set a value to entry [row, column]
set(int, int, String) - Method in class net.librec.math.structure.SparseStringMatrix
Set a value to entry [row, column]
set(double, int...) - Method in class net.librec.math.structure.SparseTensor
Set a value to a specific i-entry
set(int, double) - Method in class net.librec.math.structure.SparseVector
Set a value to entry [idx]
set(int, int, double) - Method in class net.librec.math.structure.SymmMatrix
set a value to entry (row, col)
set(double) - Method in interface net.librec.math.structure.TensorEntry
Sets the value at the current index
set(double) - Method in interface net.librec.math.structure.VectorEntry
Sets the value at the current index
setAll(double) - Method in class net.librec.math.structure.DenseMatrix
Set a value to all entries
setAll(double) - Method in class net.librec.math.structure.DenseVector
Set a value to all entries
setBoolean(String, boolean) - Method in class net.librec.conf.Configuration
Set the value of the name property to a boolean.
setColumnSet(Set<String>) - Method in class net.librec.data.model.ArffAttribute
Set attribute column set.
setConf(Configuration) - Method in class net.librec.common.AbstractContext
 
setConf(Configuration) - Method in interface net.librec.common.LibrecContext
set Configuration
setConf(Configuration) - Method in interface net.librec.conf.Configurable
Set the configuration to be used by this object.
setConf(Configuration) - Method in class net.librec.conf.Configured
 
setConf(Object, Configuration) - Static method in class net.librec.util.ReflectionUtil
Check and set 'configuration' if necessary.
setContext(RecommenderContext) - Method in class net.librec.recommender.AbstractRecommender
set Context
setContext(RecommenderContext) - Method in interface net.librec.recommender.Recommender
set Context
setContext(RecommenderContext) - Method in class net.librec.recommender.TensorRecommender
 
setData(double[]) - Method in class net.librec.math.structure.DenseVector
 
setDataConvertor(DataConvertor) - Method in interface net.librec.data.DataSplitter
Set the data convertor of this splitter.
setDataConvertor(DataConvertor) - Method in class net.librec.data.splitter.AbstractDataSplitter
 
setDouble(String, double) - Method in class net.librec.conf.Configuration
Set the value of the name property to a double.
setFinishTime(long) - Method in class net.librec.job.JobStatus
 
setFloat(String, float) - Method in class net.librec.conf.Configuration
Set the value of the name property to a float.
setInt(String, int) - Method in class net.librec.conf.Configuration
Set the value of the name property to an int.
setInts(String, int[]) - Method in class net.librec.conf.Configuration
Set the array of int values for the name property as as comma delimited values.
setItemDimension(int) - Method in class net.librec.math.structure.SparseTensor
 
setItemId(String) - Method in class net.librec.recommender.item.GenericRecommendedItem
 
setItemIdList(List<String>) - Method in class net.librec.filter.GenericRecommendedFilter
Set the itemId list.
setItemIdx(int) - Method in class net.librec.recommender.item.UserItemRatingEntry
 
setItemIdxList(int, List<ItemEntry<Integer, Double>>) - Method in class net.librec.recommender.item.RecommendedItemList
set the specified element to the end of this list.
setItemMappingData(BiMap<String, Integer>) - Method in class net.librec.data.convertor.appender.DocumentDataAppender
Set item mapping data.
setItemMappingData(BiMap<String, Integer>) - Method in class net.librec.data.convertor.appender.SocialDataAppender
Set item mapping data.
setItemMappingData(BiMap<String, Integer>) - Method in interface net.librec.data.DataAppender
Set item mapping data.
setJobId(String) - Method in class net.librec.job.JobStatus
 
setJobStage(String) - Method in class net.librec.job.JobStatus
 
setLong(String, long) - Method in class net.librec.conf.Configuration
Set the value of the name property to an long.
setMeasure(Measure) - Method in class net.librec.eval.Measure.MeasureValue
Set the Measure object of the MeasureValue object
setProgress(float) - Method in class net.librec.job.JobStatus
 
setRecommenderClass(String) - Method in class net.librec.job.RecommenderJob
 
setRecommenderClass(Class<Recommender>) - Method in class net.librec.job.RecommenderJob
 
setRow(int, double) - Method in class net.librec.math.structure.DenseMatrix
Set one value to a specific row.
setRow(int, DenseVector) - Method in class net.librec.math.structure.DenseMatrix
Set values of one dense vector to a specific row.
setSimilarity(RecommenderSimilarity) - Method in class net.librec.recommender.RecommenderContext
 
setStartTime(long) - Method in class net.librec.job.JobStatus
 
setStrings(String, String...) - Method in class net.librec.conf.Configuration
Set the array of string values for the name property as as comma delimited values.
setTimeUnit(TimeUnit) - Method in class net.librec.data.convertor.TextDataConvertor
Set the time unit of the data file.
setTopN(int) - Method in class net.librec.eval.AbstractRecommenderEvaluator
Set the number of recommended items.
setTopN(Integer) - Method in class net.librec.eval.Measure.MeasureValue
Set the number of items in the recommended list
setTopN(int) - Method in interface net.librec.eval.RecommenderEvaluator
Set the number of recommended items.
setup() - Method in class net.librec.recommender.AbstractRecommender
setup
setup() - Method in class net.librec.recommender.baseline.ItemAverageRecommender
 
setup() - Method in class net.librec.recommender.baseline.ItemClusterRecommender
 
setup() - Method in class net.librec.recommender.baseline.MostPopularRecommender
 
setup() - Method in class net.librec.recommender.baseline.RandomGuessRecommender
 
setup() - Method in class net.librec.recommender.baseline.UserAverageRecommender
 
setup() - Method in class net.librec.recommender.baseline.UserClusterRecommender
 
setup() - Method in class net.librec.recommender.cf.BHFreeRecommender
 
setup() - Method in class net.librec.recommender.cf.BUCMRecommender
 
setup() - Method in class net.librec.recommender.cf.ItemKNNRecommender
(non-Javadoc)
setup() - Method in class net.librec.recommender.cf.ranking.AoBPRRecommender
 
setup() - Method in class net.librec.recommender.cf.ranking.AspectModelRecommender
 
setup() - Method in class net.librec.recommender.cf.ranking.BPRRecommender
 
setup() - Method in class net.librec.recommender.cf.ranking.CLIMFRecommender
 
setup() - Method in class net.librec.recommender.cf.ranking.EALSRecommender
 
setup() - Method in class net.librec.recommender.cf.ranking.FISMaucRecommender
 
setup() - Method in class net.librec.recommender.cf.ranking.FISMrmseRecommender
 
setup() - Method in class net.librec.recommender.cf.ranking.GBPRRecommender
 
setup() - Method in class net.librec.recommender.cf.ranking.ItemBigramRecommender
 
setup() - Method in class net.librec.recommender.cf.ranking.LDARecommender
setup init member method
setup() - Method in class net.librec.recommender.cf.ranking.ListwiseMFRecommender
 
setup() - Method in class net.librec.recommender.cf.ranking.PLSARecommender
 
setup() - Method in class net.librec.recommender.cf.ranking.RankALSRecommender
 
setup() - Method in class net.librec.recommender.cf.ranking.RankSGDRecommender
 
setup() - Method in class net.librec.recommender.cf.ranking.SLIMRecommender
initialization
setup() - Method in class net.librec.recommender.cf.ranking.WBPRRecommender
 
setup() - Method in class net.librec.recommender.cf.ranking.WRMFRecommender
 
setup() - Method in class net.librec.recommender.cf.rating.AspectModelRecommender
 
setup() - Method in class net.librec.recommender.cf.rating.ASVDPlusPlusRecommender
 
setup() - Method in class net.librec.recommender.cf.rating.BiasedMFRecommender
 
setup() - Method in class net.librec.recommender.cf.rating.BPMFRecommender
 
setup() - Method in class net.librec.recommender.cf.rating.BPoissMFRecommender
 
setup() - Method in class net.librec.recommender.cf.rating.FMALSRecommender
 
setup() - Method in class net.librec.recommender.cf.rating.FMSGDRecommender
 
setup() - Method in class net.librec.recommender.cf.rating.GPLSARecommender
 
setup() - Method in class net.librec.recommender.cf.rating.LDCCRecommender
 
setup() - Method in class net.librec.recommender.cf.rating.LLORMARecommender
 
setup() - Method in class net.librec.recommender.cf.rating.NMFRecommender
 
setup() - Method in class net.librec.recommender.cf.rating.PMFRecommender
 
setup() - Method in class net.librec.recommender.cf.rating.RBMRecommender
 
setup() - Method in class net.librec.recommender.cf.rating.RFRecRecommender
 
setup() - Method in class net.librec.recommender.cf.rating.SVDPlusPlusRecommender
 
setup() - Method in class net.librec.recommender.cf.rating.URPRecommender
 
setup() - Method in class net.librec.recommender.cf.UserKNNRecommender
(non-Javadoc)
setup() - Method in class net.librec.recommender.content.EFMRecommender
 
setup() - Method in class net.librec.recommender.content.HFTRecommender
 
setup() - Method in class net.librec.recommender.context.ranking.SBPRRecommender
 
setup() - Method in class net.librec.recommender.context.rating.RSTERecommender
 
setup() - Method in class net.librec.recommender.context.rating.SocialMFRecommender
 
setup() - Method in class net.librec.recommender.context.rating.SoRecRecommender
 
setup() - Method in class net.librec.recommender.context.rating.SoRegRecommender
 
setup() - Method in class net.librec.recommender.context.rating.TimeSVDRecommender
 
setup() - Method in class net.librec.recommender.context.rating.TrustMFRecommender
 
setup() - Method in class net.librec.recommender.context.rating.TrustSVDRecommender
initial the model
setup() - Method in class net.librec.recommender.ext.AssociationRuleRecommender
setup
setup() - Method in class net.librec.recommender.ext.PersonalityDiagnosisRecommender
initialization
setup() - Method in class net.librec.recommender.ext.PRankDRecommender
initialization
setup() - Method in class net.librec.recommender.ext.SlopeOneRecommender
initialization
setup() - Method in class net.librec.recommender.FactorizationMachineRecommender
setup
setup() - Method in class net.librec.recommender.hybrid.HybridRecommender
initialization
setup() - Method in class net.librec.recommender.MatrixFactorizationRecommender
setup init member method
setup() - Method in class net.librec.recommender.ProbabilisticGraphicalRecommender
setup init member method
setup() - Method in class net.librec.recommender.SocialRecommender
 
setup() - Method in class net.librec.recommender.TensorRecommender
setup
setUserDimension(int) - Method in class net.librec.math.structure.SparseTensor
 
setUserId(String) - Method in class net.librec.recommender.item.GenericRecommendedItem
 
setUserIdList(List<String>) - Method in class net.librec.filter.GenericRecommendedFilter
Set the userId list.
setUserIdx(int) - Method in class net.librec.recommender.item.UserItemRatingEntry
 
setUserMappingData(BiMap<String, Integer>) - Method in class net.librec.data.convertor.appender.DocumentDataAppender
Set user mapping data.
setUserMappingData(BiMap<String, Integer>) - Method in class net.librec.data.convertor.appender.SocialDataAppender
Set user mapping data.
setUserMappingData(BiMap<String, Integer>) - Method in interface net.librec.data.DataAppender
Set user mapping data.
setValue(double) - Method in class net.librec.recommender.item.GenericRecommendedItem
 
setValue(V) - Method in class net.librec.recommender.item.ItemEntry
 
setValue(double) - Method in class net.librec.recommender.item.UserItemRatingEntry
 
shaffle(int[]) - Static method in class net.librec.util.Lists
Rearrange the elements of a int array in random order.
shaffle(double[]) - Static method in class net.librec.util.Lists
Rearrange the elements of a double array in random order.
shaffle(List<T>) - Static method in class net.librec.util.Lists
Shuffle the elements of a List.
shape - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrix
 
shape - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrixGR
 
shape - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseVector
 
shapePrior - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrix
 
shapePrior - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrixGR
 
shapePrior - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseVector
 
shortStr(String) - Static method in class net.librec.util.StringUtil
Return a subset of the string with given length 50.
shortStr(String, int) - Static method in class net.librec.util.StringUtil
Return a subset of the string with given length.
Shuffle - Class in net.librec.math.algorithm
 
Shuffle(SparseMatrix) - Constructor for class net.librec.math.algorithm.Shuffle
Construct a shuffle for SparseMatrix.
shuffle() - Method in class net.librec.math.structure.SparseTensor
Shuffle a sparse tensor
shuffleCursor - Variable in class net.librec.math.structure.SparseMatrix
 
shuffleRow - Variable in class net.librec.math.structure.SparseMatrix
 
similarities - Variable in class net.librec.eval.AbstractRecommenderEvaluator
all similarity maps
similarities - Variable in class net.librec.recommender.RecommenderContext
 
similarity - Variable in class net.librec.recommender.RecommenderContext
 
similarityMatrix - Variable in class net.librec.eval.AbstractRecommenderEvaluator
default similarityMatrix
similarityMatrix - Variable in class net.librec.similarity.AbstractRecommenderSimilarity
Similarity Matrix
size() - Method in interface net.librec.math.structure.DataSet
 
size() - Method in class net.librec.math.structure.DenseMatrix
 
size - Variable in class net.librec.math.structure.DenseVector
 
size() - Method in class net.librec.math.structure.SparseMatrix
 
size() - Method in class net.librec.math.structure.SparseTensor
 
size() - Method in class net.librec.math.structure.SparseVector
 
size - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseVector
 
size() - Method in class net.librec.recommender.item.RecommendedItemList
 
size() - Method in interface net.librec.recommender.item.RecommendedList
Returns the number of elements in this list.
slice(int, int, int...) - Method in class net.librec.math.structure.SparseTensor
Slice is a two-dimensional sub-array of a tensor, defined by fixing all but two indices.
SLIMRecommender - Class in net.librec.recommender.cf.ranking
Xia Ning and George Karypis, SLIM: Sparse Linear Methods for Top-N Recommender Systems, ICDM 2011.
SLIMRecommender() - Constructor for class net.librec.recommender.cf.ranking.SLIMRecommender
 
SlopeOneRecommender - Class in net.librec.recommender.ext
Weighted Slope One: Lemire and Maclachlan, Slope One Predictors for Online Rating-Based Collaborative Filtering , SDM 2005.
SlopeOneRecommender() - Constructor for class net.librec.recommender.ext.SlopeOneRecommender
 
smallValue - Static variable in class net.librec.recommender.cf.rating.AspectModelRecommender
 
smallValue - Static variable in class net.librec.recommender.cf.rating.GPLSARecommender
 
smoothWeight - Variable in class net.librec.recommender.cf.rating.GPLSARecommender
 
SocialDataAppender - Class in net.librec.data.convertor.appender
A SocialDataAppender is a class to process and store social appender data.
SocialDataAppender() - Constructor for class net.librec.data.convertor.appender.SocialDataAppender
Initializes a newly created SocialDataAppender object with null.
SocialDataAppender(Configuration) - Constructor for class net.librec.data.convertor.appender.SocialDataAppender
Initializes a newly created SocialDataAppender object with a Configuration object
socialMatrix - Variable in class net.librec.recommender.SocialRecommender
socialMatrix: social rate matrix, indicating a user is connecting to a number of other users
SocialMFRecommender - Class in net.librec.recommender.context.rating
Jamali and Ester, A matrix factorization technique with trust propagation for recommendation in social networks, RecSys 2010.
SocialMFRecommender() - Constructor for class net.librec.recommender.context.rating.SocialMFRecommender
 
SocialRecommender - Class in net.librec.recommender
Social Recommender
SocialRecommender() - Constructor for class net.librec.recommender.SocialRecommender
 
softmax(double[]) - Static method in class net.librec.math.algorithm.Maths
logistic function g(x)
SoRecRecommender - Class in net.librec.recommender.context.rating
Jamali and Ester, A matrix factorization technique with trust propagation for recommendation in social networks, RecSys 2010.
SoRecRecommender() - Constructor for class net.librec.recommender.context.rating.SoRecRecommender
 
SoRegRecommender - Class in net.librec.recommender.context.rating
Hao Ma, Dengyong Zhou, Chao Liu, Michael R.
SoRegRecommender() - Constructor for class net.librec.recommender.context.rating.SoRegRecommender
 
sortByDenseVectorValue(DenseVector) - Method in class net.librec.recommender.cf.ranking.AoBPRRecommender
 
sortItemEntryList(List<ItemEntry<K, V>>, boolean) - Static method in class net.librec.util.Lists
sort a list of objects: List<ItemEntry<K, V extends Comparable<? extends V>>
sortItemEntryList(List<ItemEntry<K, V>>) - Static method in class net.librec.util.Lists
sort a map object: List<ItemEntry<K, V extends Comparable<? extends V>>
sortItemEntryListTopK(List<ItemEntry<K, V>>, boolean, int) - Static method in class net.librec.util.Lists
sort a list of objects: List<ItemEntry<K, V extends Comparable<? extends V>>
sortItemEntryListTopK(List<ItemEntry<K, V>>, int) - Static method in class net.librec.util.Lists
sort a list object: List<ItemEntry<K, V extends Comparable<? extends V>>
sortList(List<Map.Entry<K, V>>, boolean) - Static method in class net.librec.util.Lists
sort a list of objects: List<Map.Entry<K, V extends Comparable<? extends V>>
sortList(List<Map.Entry<K, V>>) - Static method in class net.librec.util.Lists
sort a map object: List<Map.Entry<K, V extends Comparable<? extends V>>
sortList(List<Map.Entry<K, V>>, int) - Static method in class net.librec.util.Lists
sort a list object: List<Map.Entry<K, V extends Comparable<? extends V>>
sortListTopK(List<Map.Entry<K, V>>, boolean, int) - Static method in class net.librec.util.Lists
sort a list of objects: List<Map.Entry<K, V extends Comparable<? extends V>>
sortMap(Map<K, V>, boolean) - Static method in class net.librec.util.Lists
sort an Map<K, V extends Comparable<? extends V> map object
sortMap(Map<K, V>) - Static method in class net.librec.util.Lists
sort a map object: Map<K, V extends Comparable<? extends V>
SparseMatrix - Class in net.librec.math.structure
Data Structure: Sparse Matrix whose implementation is modified from M4J library.
SparseMatrix(int, int, Table<Integer, Integer, ? extends Number>) - Constructor for class net.librec.math.structure.SparseMatrix
Construct a sparse matrix with only CRS structures
SparseMatrix(int, int) - Constructor for class net.librec.math.structure.SparseMatrix
Define a sparse matrix without data, only use for transpose method
SparseMatrix(int, int, Table<Integer, Integer, ? extends Number>, Multimap<Integer, Integer>) - Constructor for class net.librec.math.structure.SparseMatrix
Construct a sparse matrix with both CRS and CCS structures
SparseMatrix(SparseMatrix) - Constructor for class net.librec.math.structure.SparseMatrix
Construct a sparse matrix from another sparse matrix
SparseMatrix(SparseStringMatrix) - Constructor for class net.librec.math.structure.SparseMatrix
 
SparseStringMatrix - Class in net.librec.math.structure
Data Structure: Sparse Matrix whose implementation is modified from M4J library.
SparseStringMatrix(int, int, Table<Integer, Integer, ? extends String>, Multimap<Integer, Integer>) - Constructor for class net.librec.math.structure.SparseStringMatrix
Construct a sparse matrix with both CRS and CCS structures
SparseStringMatrix(int, int, Table<Integer, Integer, ? extends String>) - Constructor for class net.librec.math.structure.SparseStringMatrix
Construct a sparse matrix with only CRS structures
SparseStringMatrix(SparseStringMatrix) - Constructor for class net.librec.math.structure.SparseStringMatrix
Construct a sparse matrix from another sparse matrix
sparseTensor - Variable in class net.librec.data.convertor.AbstractDataConvertor
store rate data as a sparse tensor
SparseTensor - Class in net.librec.math.structure
Data Structure: Sparse Tensor
SparseTensor(int...) - Constructor for class net.librec.math.structure.SparseTensor
Construct an empty sparse tensor
SparseTensor(int[], List<Integer>[], List<Double>) - Constructor for class net.librec.math.structure.SparseTensor
Construct a sparse tensor with indices and values
SparseVector - Class in net.librec.math.structure
Data Structure: Sparse Vector whose implementation is modified from M4J library
SparseVector(int) - Constructor for class net.librec.math.structure.SparseVector
Construct a sparse vector with its maximum capacity
SparseVector(int, int) - Constructor for class net.librec.math.structure.SparseVector
Construct a sparse vector with its maximum capacity
SparseVector(int, double[]) - Constructor for class net.librec.math.structure.SparseVector
Construct a sparse vector with its maximum capacity, filled with given data array
SparseVector(int, int[], double[]) - Constructor for class net.librec.math.structure.SparseVector
Construct a sparse vector by deeply copying with tis maximum capacity, indices to data, and data
SparseVector(int, int[], double[], int, int) - Constructor for class net.librec.math.structure.SparseVector
Construct a sparse vector by deeply copying with tis maximum capacity, indices to data, and data
SparseVector(SparseVector) - Constructor for class net.librec.math.structure.SparseVector
Construct a sparse vector by deeply copying another vector
splitData() - Method in interface net.librec.data.DataSplitter
Split the data.
splitData() - Method in class net.librec.data.splitter.GivenNDataSplitter
Split the data.
splitData() - Method in class net.librec.data.splitter.GivenTestSetDataSplitter
Split the data.
splitData(int) - Method in class net.librec.data.splitter.KCVDataSplitter
preserve the k-th validation as the test set and the rest as train set
splitData() - Method in class net.librec.data.splitter.KCVDataSplitter
Split the data.
splitData() - Method in class net.librec.data.splitter.LOOCVDataSplitter
Split the data.
splitData() - Method in class net.librec.data.splitter.RatioDataSplitter
Split the dataset according to the configuration file.
splitFolds() - Method in class net.librec.data.splitter.KCVDataSplitter
Assign the data into k folds.
splitFolds(int) - Method in class net.librec.data.splitter.KCVDataSplitter
Split the data into k folds.
standardize(boolean) - Method in class net.librec.math.structure.SparseMatrix
Standardize the matrix entries by row- or column-wise z-scores (z=(x-u)/sigma)
Stats - Class in net.librec.math.algorithm
 
Stats() - Constructor for class net.librec.math.algorithm.Stats
 
str - Variable in class net.librec.recommender.content.HFTRecommender
 
StringUtil - Class in net.librec.util
String Utility Class
StringUtil() - Constructor for class net.librec.util.StringUtil
 
subset(List<T>, int) - Static method in class net.librec.util.Lists
 
SUCCEEDED - Static variable in class net.librec.job.JobStatus
 
sum(double[]) - Static method in class net.librec.math.algorithm.Maths
 
sum(double[]) - Static method in class net.librec.math.algorithm.Stats
 
sum(Collection<? extends Number>) - Static method in class net.librec.math.algorithm.Stats
 
sum(int[]) - Static method in class net.librec.math.algorithm.Stats
 
sum(int) - Static method in class net.librec.math.algorithm.Stats
The sum from 1 to n.
sum() - Method in class net.librec.math.structure.DenseMatrix
 
sum() - Method in class net.librec.math.structure.DenseVector
 
sum() - Method in class net.librec.math.structure.SparseMatrix
 
sum() - Method in class net.librec.math.structure.SparseVector
 
sumOfColumn(int) - Method in class net.librec.math.structure.DenseMatrix
Return the sum of data entries in a column.
sumOfRow(int) - Method in class net.librec.math.structure.DenseMatrix
Return the sum of data entries in a row
sumSquare(int) - Static method in class net.librec.math.algorithm.Stats
The sum from 1^2 to n^2, with the largest value to n^3/3
SVD - Class in net.librec.math.algorithm
Singular Value Decomposition: adapted from the JAMA implementations
SVD(DenseMatrix) - Constructor for class net.librec.math.algorithm.SVD
Construct the singular value decomposition Structure to access U, S and V.
svd() - Method in class net.librec.math.structure.DenseMatrix
 
SVDPlusPlusRecommender - Class in net.librec.recommender.cf.rating
SVD++ Recommender
SVDPlusPlusRecommender() - Constructor for class net.librec.recommender.cf.rating.SVDPlusPlusRecommender
 
SymmMatrix - Class in net.librec.math.structure
 
SymmMatrix(int) - Constructor for class net.librec.math.structure.SymmMatrix
Construct a symmetric matrix
SymmMatrix(SymmMatrix) - Constructor for class net.librec.math.structure.SymmMatrix
Construct a symmetric matrix by deeply copying data from a given matrix
Systems - Class in net.librec.util
 
Systems() - Constructor for class net.librec.util.Systems
 
Systems.OS - Enum in net.librec.util
 

T

tenserKeysToFeatureVector(int[]) - Method in class net.librec.recommender.FactorizationMachineRecommender
Transform the keys of a tensor entry into a sparse vector.
TensorEntry - Interface in net.librec.math.structure
An entry of a tensor.
TensorRecommender - Class in net.librec.recommender
Tensor Recommender
TensorRecommender() - Constructor for class net.librec.recommender.TensorRecommender
 
testData - Variable in class net.librec.recommender.content.EFMRecommender
 
testDataSet - Variable in class net.librec.data.model.AbstractDataModel
test DataSet
testMatrix - Variable in class net.librec.data.splitter.AbstractDataSplitter
testMatrix
testMatrix - Variable in class net.librec.recommender.AbstractRecommender
testMatrix
testTensor - Variable in class net.librec.recommender.FactorizationMachineRecommender
testTensor
testTensor - Variable in class net.librec.recommender.TensorRecommender
testTensor
TextDataConvertor - Class in net.librec.data.convertor
A TextDataConvertor is a class to convert a data file from CSV format to a target format.
TextDataConvertor(String) - Constructor for class net.librec.data.convertor.TextDataConvertor
Initializes a newly created TextDataConvertor object with the path of the input data file.
TextDataConvertor(String, String) - Constructor for class net.librec.data.convertor.TextDataConvertor
Initializes a newly created TextDataConvertor object with the path and format of the input data file.
TextDataConvertor(String, String, double) - Constructor for class net.librec.data.convertor.TextDataConvertor
Initializes a newly created TextDataConvertor object with the path and format of the input data file.
TextDataConvertor(String, String, double, BiMap<String, Integer>, BiMap<String, Integer>) - Constructor for class net.librec.data.convertor.TextDataConvertor
Initializes a newly created TextDataConvertor object with the path and format of the input data file.
TextDataModel - Class in net.librec.data.model
A TextDataModel represents a data access class to the CSV format input.
TextDataModel() - Constructor for class net.librec.data.model.TextDataModel
Empty constructor.
TextDataModel(Configuration) - Constructor for class net.librec.data.model.TextDataModel
Initializes a newly created TextDataModel object with configuration.
theta(int) - Method in class net.librec.recommender.content.HFTRecommender
 
thetaus - Variable in class net.librec.recommender.content.HFTRecommender
 
TimeSVDRecommender - Class in net.librec.recommender.context.rating
TimeSVD++ Recommender
TimeSVDRecommender() - Constructor for class net.librec.recommender.context.rating.TimeSVDRecommender
 
toArray(Collection<? extends Number>) - Static method in class net.librec.util.Lists
Turn a collection of data into an double array
toByteArray(InputStream) - Static method in class net.librec.util.IOUtil
Get the contents of an InputStream as a byte[].
toByteArray(Reader) - Static method in class net.librec.util.IOUtil
Get the contents of a Reader as a byte[] using the default character encoding of the platform.
toByteArray(Reader, String) - Static method in class net.librec.util.IOUtil
Get the contents of a Reader as a byte[] using the specified character encoding.
toByteArray(String) - Static method in class net.librec.util.IOUtil
Deprecated.
Use String.getBytes()
toCharArray(InputStream) - Static method in class net.librec.util.IOUtil
Get the contents of an InputStream as a character array using the default character encoding of the platform.
toCharArray(InputStream, String) - Static method in class net.librec.util.IOUtil
Get the contents of an InputStream as a character array using the specified character encoding.
toCharArray(Reader) - Static method in class net.librec.util.IOUtil
Get the contents of a Reader as a character array.
toClipboard(String) - Static method in class net.librec.util.StringUtil
 
toDouble(String) - Static method in class net.librec.util.StringUtil
 
toDouble(String, double) - Static method in class net.librec.util.StringUtil
 
toFloat(String) - Static method in class net.librec.util.StringUtil
 
toFloat(String, float) - Static method in class net.librec.util.StringUtil
 
toInputStream(String) - Static method in class net.librec.util.IOUtil
Convert the specified string to an input stream, encoded as bytes using the default character encoding of the platform.
toInputStream(String, String) - Static method in class net.librec.util.IOUtil
Convert the specified string to an input stream, encoded as bytes using the specified character encoding.
toInt(String) - Static method in class net.librec.util.StringUtil
 
toInt(String, int) - Static method in class net.librec.util.StringUtil
 
toList(double[]) - Static method in class net.librec.util.Lists
Turn an double array into a List<Double> object
toList(int[]) - Static method in class net.librec.util.Lists
Convert int array to int list
toList(String, String) - Static method in class net.librec.util.StringUtil
Split the given string str into a list of strings with separated by reg
toLong(String) - Static method in class net.librec.util.StringUtil
 
toLong(String, long) - Static method in class net.librec.util.StringUtil
 
toMap() - Method in class net.librec.math.structure.SparseVector
 
topicAssignment - Variable in class net.librec.recommender.content.HFTRecommender
 
topicAssignments - Variable in class net.librec.recommender.cf.ranking.ItemBigramRecommender
entry[u, i, k]: topic assignment as sparse structure
topicAssignments - Variable in class net.librec.recommender.cf.ranking.LDARecommender
topic assignment as list from the iterator of trainMatrix
topicItemMu - Variable in class net.librec.recommender.cf.rating.GPLSARecommender
 
topicItemNumbers - Variable in class net.librec.recommender.cf.ranking.LDARecommender
entry[k, i]: number of tokens assigned to topic k, given item i.
topicItemProbs - Variable in class net.librec.recommender.cf.ranking.AspectModelRecommender
Conditional distribution: P(i|z)
topicItemProbs - Variable in class net.librec.recommender.cf.ranking.LDARecommender
posterior probabilities of parameters
topicItemProbs - Variable in class net.librec.recommender.cf.ranking.PLSARecommender
Conditional Probability: P(i|z)
topicItemProbs - Variable in class net.librec.recommender.cf.rating.AspectModelRecommender
 
topicItemProbsSum - Variable in class net.librec.recommender.cf.ranking.AspectModelRecommender
Conditional distribution: P(i|z)
topicItemProbsSum - Variable in class net.librec.recommender.cf.ranking.LDARecommender
cumulative statistics of theta, phi
topicItemProbsSum - Variable in class net.librec.recommender.cf.ranking.PLSARecommender
Conditional Probability: P(i|z)
topicItemProbsSum - Variable in class net.librec.recommender.cf.rating.AspectModelRecommender
 
topicItemRatingProbs - Variable in class net.librec.recommender.cf.rating.URPRecommender
posterior probabilities of parameters phi_{k, i, r}
topicItemSigma - Variable in class net.librec.recommender.cf.rating.GPLSARecommender
 
topicProbs - Variable in class net.librec.recommender.cf.ranking.AspectModelRecommender
topic distribution: P(z)
topicProbs - Variable in class net.librec.recommender.cf.rating.AspectModelRecommender
 
topicProbsMean - Variable in class net.librec.recommender.cf.rating.AspectModelRecommender
 
topicProbsMeanSum - Variable in class net.librec.recommender.cf.rating.AspectModelRecommender
 
topicProbsSum - Variable in class net.librec.recommender.cf.ranking.AspectModelRecommender
topic distribution: P(z)
topicProbsSum - Variable in class net.librec.recommender.cf.rating.AspectModelRecommender
 
topicProbsVariance - Variable in class net.librec.recommender.cf.rating.AspectModelRecommender
 
topicProbsVarianceSum - Variable in class net.librec.recommender.cf.rating.AspectModelRecommender
 
topics - Variable in class net.librec.recommender.cf.BUCMRecommender
 
topics - Variable in class net.librec.recommender.cf.rating.URPRecommender
 
topicTokenNumbers - Variable in class net.librec.recommender.cf.ranking.LDARecommender
entry[k]: number of tokens assigned to topic t.
topicToWord - Variable in class net.librec.recommender.content.HFTRecommender
 
topicUserProbs - Variable in class net.librec.recommender.cf.ranking.AspectModelRecommender
Conditional distribution: P(u|z)
topicUserProbs - Variable in class net.librec.recommender.cf.rating.AspectModelRecommender
 
topicUserProbsSum - Variable in class net.librec.recommender.cf.ranking.AspectModelRecommender
Conditional distribution: P(u|z)
topicUserProbsSum - Variable in class net.librec.recommender.cf.rating.AspectModelRecommender
 
topN - Variable in class net.librec.eval.AbstractRecommenderEvaluator
the number of recommended items
topN - Variable in class net.librec.math.structure.DenseMatrix
dimension
topN - Variable in class net.librec.recommender.AbstractRecommender
topN
topN - Variable in class net.librec.recommender.TensorRecommender
topN
topNRank(int) - Method in class net.librec.recommender.item.RecommendedItemList
top n ranked Items for all userIdx
topNRank(int) - Method in interface net.librec.recommender.item.RecommendedList
top n ranked Items for all userIdx
topNRankItemsByUser(int, int) - Method in class net.librec.recommender.item.RecommendedItemList
top n ranked Items at user userIdx
topNRankItemsByUser(int, int) - Method in interface net.librec.recommender.item.RecommendedList
top n ranked Items at user userIdx
toSection(List<String>) - Static method in class net.librec.util.StringUtil
convert to a section of message
toString() - Method in class net.librec.conf.Configuration.Resource
 
toString() - Method in class net.librec.math.structure.DenseMatrix
 
toString() - Method in class net.librec.math.structure.DenseVector
 
toString() - Method in class net.librec.math.structure.SparseMatrix
 
toString() - Method in class net.librec.math.structure.SparseTensor
 
toString() - Method in class net.librec.math.structure.SparseVector
 
toString() - Method in class net.librec.math.structure.SymmMatrix
 
toString() - Method in class net.librec.recommender.item.ItemEntry
 
toString(long, String) - Static method in class net.librec.util.DateUtil
Parse the milliseconds date to string with simple date pattern.
toString(long) - Static method in class net.librec.util.DateUtil
Parse the milliseconds date to string with specified pattern.
toString(InputStream) - Static method in class net.librec.util.IOUtil
Get the contents of an InputStream as a String using the default character encoding of the platform.
toString(InputStream, String) - Static method in class net.librec.util.IOUtil
Get the contents of an InputStream as a String using the specified character encoding.
toString(Reader) - Static method in class net.librec.util.IOUtil
Get the contents of a Reader as a String.
toString(byte[]) - Static method in class net.librec.util.IOUtil
Deprecated.
Use String.String(byte[])
toString(byte[], String) - Static method in class net.librec.util.IOUtil
Deprecated.
Use String.String(byte[], String)
toString(Object[], String) - Static method in class net.librec.util.StringUtil
Concatenates an array of string
toString(Object[]) - Static method in class net.librec.util.StringUtil
default sep="," between all objects
toString(double) - Static method in class net.librec.util.StringUtil
Parse a double data into string
toString(long) - Static method in class net.librec.util.StringUtil
Parse a long data into string
toString(double[][]) - Static method in class net.librec.util.StringUtil
Parse a double[][] data into string
toString(int[][]) - Static method in class net.librec.util.StringUtil
Parse a int[][] data into string
toString(Number, int) - Static method in class net.librec.util.StringUtil
Parse a Number data into string
toString(Collection<T>) - Static method in class net.librec.util.StringUtil
Parse a Collection<T> data into string
toString(Collection<T>, String) - Static method in class net.librec.util.StringUtil
Parse a Collection<T> data into string
toString(Map<K, V>) - Static method in class net.librec.util.StringUtil
Parse a Map<K, V> data into string
toString(Map<K, V>, String) - Static method in class net.librec.util.StringUtil
Parse a Map<K, V> data into string
toString(double[]) - Static method in class net.librec.util.StringUtil
Parse a double[] data into string
toString(int[]) - Static method in class net.librec.util.StringUtil
Parse a int[] data into string
trainData - Variable in class net.librec.recommender.content.EFMRecommender
 
trainDataSet - Variable in class net.librec.data.model.AbstractDataModel
train DataSet
trainMatrix - Variable in class net.librec.data.splitter.AbstractDataSplitter
trainMatrix
trainMatrix - Variable in class net.librec.recommender.AbstractRecommender
trainMatrix
trainModel() - Method in class net.librec.recommender.AbstractRecommender
train Model
trainModel() - Method in class net.librec.recommender.baseline.ConstantGuessRecommender
 
trainModel() - Method in class net.librec.recommender.baseline.GlobalAverageRecommender
 
trainModel() - Method in class net.librec.recommender.baseline.ItemAverageRecommender
 
trainModel() - Method in class net.librec.recommender.baseline.MostPopularRecommender
 
trainModel() - Method in class net.librec.recommender.baseline.RandomGuessRecommender
 
trainModel() - Method in class net.librec.recommender.baseline.UserAverageRecommender
 
trainModel() - Method in class net.librec.recommender.cf.ItemKNNRecommender
(non-Javadoc)
trainModel() - Method in class net.librec.recommender.cf.ranking.AoBPRRecommender
 
trainModel() - Method in class net.librec.recommender.cf.ranking.BPRRecommender
 
trainModel() - Method in class net.librec.recommender.cf.ranking.CLIMFRecommender
 
trainModel() - Method in class net.librec.recommender.cf.ranking.EALSRecommender
 
trainModel() - Method in class net.librec.recommender.cf.ranking.FISMaucRecommender
 
trainModel() - Method in class net.librec.recommender.cf.ranking.FISMrmseRecommender
 
trainModel() - Method in class net.librec.recommender.cf.ranking.GBPRRecommender
 
trainModel() - Method in class net.librec.recommender.cf.ranking.ListwiseMFRecommender
 
trainModel() - Method in class net.librec.recommender.cf.ranking.RankALSRecommender
 
trainModel() - Method in class net.librec.recommender.cf.ranking.RankSGDRecommender
 
trainModel() - Method in class net.librec.recommender.cf.ranking.SLIMRecommender
train model
trainModel() - Method in class net.librec.recommender.cf.ranking.WBPRRecommender
 
trainModel() - Method in class net.librec.recommender.cf.ranking.WRMFRecommender
 
trainModel() - Method in class net.librec.recommender.cf.rating.AspectModelRecommender
 
trainModel() - Method in class net.librec.recommender.cf.rating.ASVDPlusPlusRecommender
 
trainModel() - Method in class net.librec.recommender.cf.rating.BiasedMFRecommender
 
trainModel() - Method in class net.librec.recommender.cf.rating.BPMFRecommender
 
trainModel() - Method in class net.librec.recommender.cf.rating.BPoissMFRecommender
 
trainModel() - Method in class net.librec.recommender.cf.rating.FMALSRecommender
 
trainModel() - Method in class net.librec.recommender.cf.rating.FMSGDRecommender
 
trainModel() - Method in class net.librec.recommender.cf.rating.GPLSARecommender
 
trainModel() - Method in class net.librec.recommender.cf.rating.LLORMARecommender
 
trainModel() - Method in class net.librec.recommender.cf.rating.MFALSRecommender
 
trainModel() - Method in class net.librec.recommender.cf.rating.NMFRecommender
 
trainModel() - Method in class net.librec.recommender.cf.rating.PMFRecommender
 
trainModel() - Method in class net.librec.recommender.cf.rating.RBMRecommender
 
trainModel() - Method in class net.librec.recommender.cf.rating.RFRecRecommender
 
trainModel() - Method in class net.librec.recommender.cf.rating.SVDPlusPlusRecommender
 
trainModel() - Method in class net.librec.recommender.cf.UserKNNRecommender
(non-Javadoc)
trainModel() - Method in class net.librec.recommender.content.EFMRecommender
 
trainModel() - Method in class net.librec.recommender.content.HFTRecommender
 
trainModel() - Method in class net.librec.recommender.context.ranking.SBPRRecommender
 
trainModel() - Method in class net.librec.recommender.context.rating.RSTERecommender
 
trainModel() - Method in class net.librec.recommender.context.rating.SocialMFRecommender
 
trainModel() - Method in class net.librec.recommender.context.rating.SoRecRecommender
 
trainModel() - Method in class net.librec.recommender.context.rating.SoRegRecommender
 
trainModel() - Method in class net.librec.recommender.context.rating.TimeSVDRecommender
 
trainModel() - Method in class net.librec.recommender.context.rating.TrustMFRecommender
 
trainModel() - Method in class net.librec.recommender.context.rating.TrustSVDRecommender
train model process
trainModel() - Method in class net.librec.recommender.ext.AssociationRuleRecommender
 
trainModel() - Method in class net.librec.recommender.ext.ExternalRecommender
 
trainModel() - Method in class net.librec.recommender.ext.PersonalityDiagnosisRecommender
train model
trainModel() - Method in class net.librec.recommender.ext.PRankDRecommender
train model
trainModel() - Method in class net.librec.recommender.ext.SlopeOneRecommender
train model
trainModel() - Method in class net.librec.recommender.hybrid.HybridRecommender
train model
trainModel() - Method in class net.librec.recommender.ProbabilisticGraphicalRecommender
 
trainModel() - Method in class net.librec.recommender.TensorRecommender
train Model
trainTensor - Variable in class net.librec.recommender.FactorizationMachineRecommender
train Tensor
trainTensor - Variable in class net.librec.recommender.TensorRecommender
train Tensor
transform(K) - Method in interface net.librec.util.FileUtil.Converter
 
transMult() - Method in class net.librec.math.structure.DenseMatrix
 
transpose() - Method in class net.librec.math.structure.DenseMatrix
 
transpose() - Method in class net.librec.math.structure.SparseMatrix
 
transpose() - Method in class net.librec.math.structure.SparseStringMatrix
 
TRIANGULAR_KERNEL - Static variable in class net.librec.math.algorithm.KernelSmoothing
 
trusteeItemFactors - Variable in class net.librec.recommender.context.rating.TrustMFRecommender
trustee model
TrusteeMF() - Method in class net.librec.recommender.context.rating.TrustMFRecommender
Build TrusteeMF model: We*Ve
trusteeUserTrusteeFactors - Variable in class net.librec.recommender.context.rating.TrustMFRecommender
trustee model
trusteeUserTrusterFactors - Variable in class net.librec.recommender.context.rating.TrustMFRecommender
trustee model
trusterItemFactors - Variable in class net.librec.recommender.context.rating.TrustMFRecommender
truster model
TrusterMF() - Method in class net.librec.recommender.context.rating.TrustMFRecommender
Build TrusterMF model: Br*Vr
trusterUserTrusteeFactors - Variable in class net.librec.recommender.context.rating.TrustMFRecommender
truster model
trusterUserTrusterFactors - Variable in class net.librec.recommender.context.rating.TrustMFRecommender
truster model
TrustMFRecommender - Class in net.librec.recommender.context.rating
Yang et al., Social Collaborative Filtering by Trust, IJCAI 2013.
TrustMFRecommender() - Constructor for class net.librec.recommender.context.rating.TrustMFRecommender
 
TrustSVDRecommender - Class in net.librec.recommender.context.rating
Guo et al., TrustSVD: Collaborative Filtering with Both the Explicit and Implicit Influence of User Trust and of Item Ratings, AAAI 2015.
TrustSVDRecommender() - Constructor for class net.librec.recommender.context.rating.TrustSVDRecommender
 

U

uniform(int) - Static method in class net.librec.math.algorithm.Randoms
Random generate an integer in [0, range)
uniform(int, int) - Static method in class net.librec.math.algorithm.Randoms
Random generate an integer in [min, max)
uniform() - Static method in class net.librec.math.algorithm.Randoms
Random (uniformly distributed) double in [0, 1)
uniform(double, double) - Static method in class net.librec.math.algorithm.Randoms
Random (uniformly distributed) double in [min, max)
UNIFORM_KERNEL - Static variable in class net.librec.math.algorithm.KernelSmoothing
 
updateLRate(int) - Method in class net.librec.recommender.context.rating.TrustMFRecommender
This is the method used by the paper authors
updateLRate(int) - Method in class net.librec.recommender.MatrixFactorizationRecommender
Update current learning rate after each epoch
bold driver: Gemulla et al., Large-scale matrix factorization with distributed stochastic gradient descent, KDD 2011. constant decay: Niu et al, Hogwild!: A lock-free approach to parallelizing stochastic gradient descent, NIPS 2011. Leon Bottou, Stochastic Gradient Descent Tricks more ways to adapt learning rate can refer to: http://www.willamette.edu/~gorr/classes/cs449/momrate.html
updateLRate(int) - Method in class net.librec.recommender.TensorRecommender
Update current learning rate after each epoch
bold driver: Gemulla et al., Large-scale matrix factorization with distributed stochastic gradient descent, KDD 2011. constant decay: Niu et al, Hogwild!: A lock-free approach to parallelizing stochastic gradient descent, NIPS 2011. Leon Bottou, Stochastic Gradient Descent Tricks more ways to adapt learning rate can refer to: http://www.willamette.edu/~gorr/classes/cs449/momrate.html
updateParameters(DenseMatrix, SparseVector, BPMFRecommender.HyperParameters) - Method in class net.librec.recommender.cf.rating.BPMFRecommender
 
updateRankingInFactor() - Method in class net.librec.recommender.cf.ranking.AoBPRRecommender
 
URLReader - Class in net.librec.util
 
URLReader() - Constructor for class net.librec.util.URLReader
 
URPRecommender - Class in net.librec.recommender.cf.rating
User Rating Profile: a LDA model for rating prediction.
URPRecommender() - Constructor for class net.librec.recommender.cf.rating.URPRecommender
 
USER_DIRECTORY - Static variable in class net.librec.util.Systems
 
USER_NAME - Static variable in class net.librec.util.Systems
 
UserAverageRecommender - Class in net.librec.recommender.baseline
Baseline: predict by the average of target user's ratings
UserAverageRecommender() - Constructor for class net.librec.recommender.baseline.UserAverageRecommender
 
userBiases - Variable in class net.librec.recommender.cf.rating.BiasedMFRecommender
user biases
userCache - Variable in class net.librec.recommender.ext.AssociationRuleRecommender
user-vector cache, item-vector cache
UserClusterRecommender - Class in net.librec.recommender.baseline
It is a graphical model that clusters users into K groups for recommendation, see reference: Barbieri et al., Probabilistic Approaches to Recommendations (Section 2.2), Synthesis Lectures on Data Mining and Knowledge Discovery, 2014.
UserClusterRecommender() - Constructor for class net.librec.recommender.baseline.UserClusterRecommender
 
userDimension - Variable in class net.librec.recommender.TensorRecommender
user and item index of tensor
userExp - Variable in class net.librec.recommender.cf.ranking.ListwiseMFRecommender
 
userFactors - Variable in class net.librec.recommender.MatrixFactorizationRecommender
user latent factors
userFeatureAttention - Variable in class net.librec.recommender.content.EFMRecommender
 
userFeatureMatrix - Variable in class net.librec.recommender.content.EFMRecommender
 
userHiddenMatrix - Variable in class net.librec.recommender.content.EFMRecommender
 
UserItemRatingEntry - Class in net.librec.recommender.item
 
UserItemRatingEntry() - Constructor for class net.librec.recommender.item.UserItemRatingEntry
 
UserItemRatingEntry(int, int, double) - Constructor for class net.librec.recommender.item.UserItemRatingEntry
 
userItemsCache - Variable in class net.librec.recommender.cf.ranking.FISMaucRecommender
user-items cache, item-users cache
userItemsCache - Variable in class net.librec.recommender.cf.ranking.FISMrmseRecommender
user-items cache, item-users cache
userItemsCache - Variable in class net.librec.recommender.cf.ranking.GBPRRecommender
user-items cache, item-users cache
userItemsCache - Variable in class net.librec.recommender.cf.ranking.WBPRRecommender
user-items cache, item-users cache
userItemsCache - Variable in class net.librec.recommender.context.ranking.SBPRRecommender
user-items cache, item-users cache
userItemsCache - Variable in class net.librec.recommender.context.rating.TrustSVDRecommender
user-items cache, user-trustee cache
userItemsList - Variable in class net.librec.recommender.cf.rating.ASVDPlusPlusRecommender
user items list
userItemsList - Variable in class net.librec.recommender.cf.rating.SVDPlusPlusRecommender
user items list
userIterator() - Method in class net.librec.recommender.item.RecommendedItemList
get the iterator of user index
userIterator() - Method in interface net.librec.recommender.item.RecommendedList
get the iterator of user index
UserKNNRecommender - Class in net.librec.recommender.cf
UserKNNRecommender
UserKNNRecommender() - Constructor for class net.librec.recommender.cf.UserKNNRecommender
 
userMappingData - Variable in class net.librec.recommender.AbstractRecommender
user Mapping Data
userMappingData - Variable in class net.librec.recommender.TensorRecommender
user Mapping Data
userMu - Variable in class net.librec.recommender.cf.rating.GPLSARecommender
 
userSigma - Variable in class net.librec.recommender.cf.rating.GPLSARecommender
 
userTokenNumbers - Variable in class net.librec.recommender.cf.ranking.ItemBigramRecommender
entry[u]: number of tokens rated by user u.
userTokenNumbers - Variable in class net.librec.recommender.cf.ranking.LDARecommender
entry[u]: number of tokens rated by user u.
userTopicNumbers - Variable in class net.librec.recommender.cf.ranking.ItemBigramRecommender
entry[u, k]: number of tokens assigned to topic k, given user u.
userTopicNumbers - Variable in class net.librec.recommender.cf.ranking.LDARecommender
entry[u, k]: number of tokens assigned to topic k, given user u.
userTopicProbs - Variable in class net.librec.recommender.cf.ranking.ItemBigramRecommender
posterior probabilities of parameters
userTopicProbs - Variable in class net.librec.recommender.cf.ranking.LDARecommender
posterior probabilities of parameters
userTopicProbs - Variable in class net.librec.recommender.cf.ranking.PLSARecommender
Conditional Probability: P(z|u)
userTopicProbs - Variable in class net.librec.recommender.cf.rating.GPLSARecommender
 
userTopicProbsSum - Variable in class net.librec.recommender.cf.ranking.ItemBigramRecommender
cumulative statistics of theta, phi
userTopicProbsSum - Variable in class net.librec.recommender.cf.ranking.LDARecommender
cumulative statistics of theta, phi
userTopicProbsSum - Variable in class net.librec.recommender.cf.ranking.PLSARecommender
Conditional Probability: P(z|u)
userTrusteeCache - Variable in class net.librec.recommender.context.rating.TrustSVDRecommender
user-items cache, user-trustee cache

V

V - Variable in class net.librec.recommender.FactorizationMachineRecommender
parameter matrix
validationMatrix - Variable in class net.librec.data.splitter.AbstractDataSplitter
validationMatrix
validDataSet - Variable in class net.librec.data.model.AbstractDataModel
valid DataSet
validMatrix - Variable in class net.librec.recommender.AbstractRecommender
validMatrix
validTensor - Variable in class net.librec.recommender.FactorizationMachineRecommender
validTensor
validTensor - Variable in class net.librec.recommender.TensorRecommender
validTensor
value(int) - Method in class net.librec.math.structure.SparseTensor
Return value in a given index.
value - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrix
 
value - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseMatrixGR
 
value - Variable in class net.librec.recommender.cf.rating.BPoissMFRecommender.GammaDenseVector
 
valueOf(String) - Static method in enum net.librec.data.DataSplitter.SplitterType
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum net.librec.eval.Measure
Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum net.librec.util.Systems.OS
Returns the enum constant of this type with the specified name.
values() - Static method in enum net.librec.data.DataSplitter.SplitterType
Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum net.librec.eval.Measure
Returns an array containing the constants of this enum type, in the order they are declared.
values - Variable in class net.librec.math.structure.SparseTensor
 
values() - Static method in enum net.librec.util.Systems.OS
Returns an array containing the constants of this enum type, in the order they are declared.
var(double[]) - Static method in class net.librec.math.algorithm.Stats
Calculate a sample's variance.
var(double[], double) - Static method in class net.librec.math.algorithm.Stats
Calculate a sample's variance
variance - Variable in class net.librec.recommender.cf.rating.BPMFRecommender.HyperParameters
 
VectorEntry - Interface in net.librec.math.structure
An entry of a vector.
verbose - Static variable in class net.librec.recommender.AbstractRecommender
verbose
verbose - Variable in class net.librec.recommender.TensorRecommender
verbose

W

W - Variable in class net.librec.recommender.FactorizationMachineRecommender
weight vector
w0 - Variable in class net.librec.recommender.FactorizationMachineRecommender
global bias
WBPRRecommender - Class in net.librec.recommender.cf.ranking
Gantner et al., Bayesian Personalized Ranking for Non-Uniformly Sampled Items, JMLR, 2012.
WBPRRecommender() - Constructor for class net.librec.recommender.cf.ranking.WBPRRecommender
 
weightCoefficient - Variable in class net.librec.recommender.cf.ranking.EALSRecommender
confidence weight coefficient for WRMF
weightCoefficient - Variable in class net.librec.recommender.cf.ranking.WRMFRecommender
confidence weight coefficient
weightedcMean(double[], double[]) - Static method in class net.librec.math.algorithm.Stats
 
wishart(DenseMatrix, double) - Static method in class net.librec.math.algorithm.Randoms
Randomly sample a matrix from Wishart Distribution with the given parameters.
WORKING_DIRECTORY - Static variable in class net.librec.util.Systems
 
write(byte[], OutputStream) - Static method in class net.librec.util.IOUtil
Writes bytes from a byte[] to an OutputStream.
write(byte[], Writer) - Static method in class net.librec.util.IOUtil
Writes bytes from a byte[] to chars on a Writer using the default character encoding of the platform.
write(byte[], Writer, String) - Static method in class net.librec.util.IOUtil
Writes bytes from a byte[] to chars on a Writer using the specified character encoding.
write(char[], Writer) - Static method in class net.librec.util.IOUtil
Writes chars from a char[] to a Writer using the default character encoding of the platform.
write(char[], OutputStream) - Static method in class net.librec.util.IOUtil
Writes chars from a char[] to bytes on an OutputStream.
write(char[], OutputStream, String) - Static method in class net.librec.util.IOUtil
Writes chars from a char[] to bytes on an OutputStream using the specified character encoding.
write(String, Writer) - Static method in class net.librec.util.IOUtil
Writes chars from a String to a Writer.
write(String, OutputStream) - Static method in class net.librec.util.IOUtil
Writes chars from a String to bytes on an OutputStream using the default character encoding of the platform.
write(String, OutputStream, String) - Static method in class net.librec.util.IOUtil
Writes chars from a String to bytes on an OutputStream using the specified character encoding.
write(StringBuffer, Writer) - Static method in class net.librec.util.IOUtil
Writes chars from a StringBuffer to a Writer.
write(StringBuffer, OutputStream) - Static method in class net.librec.util.IOUtil
Writes chars from a StringBuffer to bytes on an OutputStream using the default character encoding of the platform.
write(StringBuffer, OutputStream, String) - Static method in class net.librec.util.IOUtil
Writes chars from a StringBuffer to bytes on an OutputStream using the specified character encoding.
writeLines(Collection, String, OutputStream) - Static method in class net.librec.util.IOUtil
Writes the toString() value of each item in a collection to an OutputStream line by line, using the default character encoding of the platform and the specified line ending.
writeLines(Collection, String, OutputStream, String) - Static method in class net.librec.util.IOUtil
Writes the toString() value of each item in a collection to an OutputStream line by line, using the specified character encoding and the specified line ending.
writeLines(Collection, String, Writer) - Static method in class net.librec.util.IOUtil
Writes the toString() value of each item in a collection to a Writer line by line, using the specified line ending.
writeList(String, Collection<T>) - Static method in class net.librec.util.FileUtil
Write contents in Collection<T> to a file.
writeList(String, Collection<T>, boolean) - Static method in class net.librec.util.FileUtil
Write contents in Collection<T> to a file.
writeList(String, Collection<T>, FileUtil.Converter<T, String>, boolean) - Static method in class net.librec.util.FileUtil
Write contents in Collection<T> to a file with the help of a writer helper.
writeListSyn(String, List<T>) - Static method in class net.librec.util.FileUtil
Write contents in Collection<T> to a file.
writeString(String, String) - Static method in class net.librec.util.FileUtil
Write a string into a file
writeString(String, String, boolean) - Static method in class net.librec.util.FileUtil
Write a string into a file with the given path and content.
writeVector(String, List<T>) - Static method in class net.librec.util.FileUtil
Write contents in List<T> to a file.
writeVector(String, List<T>, FileUtil.Converter<T, String>, boolean) - Static method in class net.librec.util.FileUtil
Write contents in List<T> to a file with the help of a writer helper.
WRMFRecommender - Class in net.librec.recommender.cf.ranking
WRMF: Weighted Regularized Matrix Factorization.
WRMFRecommender() - Constructor for class net.librec.recommender.cf.ranking.WRMFRecommender
 

Y

Y - Variable in class net.librec.recommender.content.HFTRecommender
 

Z

zero - Static variable in class net.librec.math.algorithm.Maths
 
zero(double[], int) - Static method in class net.librec.util.ZeroSetter
set all the elements of a double vector to zero
zero(int[], int) - Static method in class net.librec.util.ZeroSetter
set all the elements of a integer vector to zero
zero(int[][], int, int) - Static method in class net.librec.util.ZeroSetter
set all the elements of a integer matrix to zero
zero(double[][], int, int) - Static method in class net.librec.util.ZeroSetter
set all the elements of a double matrix to zero
zero(double[][][], int, int, int) - Static method in class net.librec.util.ZeroSetter
set all the elements of a double tensor to zero
zeroCount - Variable in class net.librec.math.structure.SparseVector
 
zeroFirstIndex - Variable in class net.librec.math.structure.SparseVector
 
ZeroSetter - Class in net.librec.util
This class sets vector or matrix or tensor to zero
ZeroSetter() - Constructor for class net.librec.util.ZeroSetter
 
zipFolder(String, String) - Static method in class net.librec.util.FileUtil
Zip a given folder
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