- 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
- allFeaturesMappingData - Variable in class net.librec.recommender.TensorRecommender
-
- 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
-
- 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
- calculatePhis() - Method in class net.librec.recommender.content.HFTRecommender
-
- calculateThetas() - Method in class net.librec.recommender.content.HFTRecommender
-
- 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
-
- 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
-
- Configuration.Resource(Object) - Constructor for class net.librec.conf.Configuration.Resource
-
- Configuration.Resource(Object, String) - Constructor for class net.librec.conf.Configuration.Resource
-
- 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, int) - Method in class net.librec.math.structure.SymmMatrix
-
Get a value at entry (row, col)
- 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.
- 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
-
- 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
-
- 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
-
- 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
-
- 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.
- 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
- getAllFeaturesMappingData() - Method in class net.librec.data.model.ArffDataModel
-
Get all features mapping data.
- 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.
- getLoss(DenseMatrix, DenseMatrix) - Method in class net.librec.recommender.cf.ranking.ListRankMFRecommender
-
- 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 class net.librec.recommender.content.EFMRecommender
-
- getRecommendedList() - Method in class net.librec.recommender.content.HFTRecommender
-
- 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 String
s.
- 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 String
s, 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.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
-
- 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.content.EFMRecommender
-
init mean
- initMean - Variable in class net.librec.recommender.content.HFTRecommender
-
init mean
- 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.content.EFMRecommender
-
init standard deviation
- initStd - Variable in class net.librec.recommender.content.HFTRecommender
-
init standard deviation
- 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.ProbabilisticGraphicalRecommender
-
- 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
- itemBiases - Variable in class net.librec.recommender.content.HFTRecommender
-
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.content.EFMRecommender
-
item latent factors
- itemFactors - Variable in class net.librec.recommender.content.HFTRecommender
-
item latent factors
- 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
-
- 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.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
- ListRankMFRecommender - Class in net.librec.recommender.cf.ranking
-
Shi et al., List-wise learning to rank with matrix factorization for
collaborative filtering, RecSys 2010.
- ListRankMFRecommender() - Constructor for class net.librec.recommender.cf.ranking.ListRankMFRecommender
-
- Lists - Class in net.librec.util
-
This class is for the operations of arrays or collections
- Lists() - Constructor for class net.librec.util.Lists
-
- 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
- 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
-
- Measure.MeasureValue(Measure) - Constructor for class net.librec.eval.Measure.MeasureValue
-
Construct with the measure type of the value.
- Measure.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
- 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
-
- 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.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[]) - Method in class net.librec.recommender.content.EFMRecommender
-
- predict(int, int) - Method in class net.librec.recommender.content.EFMRecommender
-
- predict(int[]) - Method in class net.librec.recommender.content.HFTRecommender
-
- 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, boolean) - Method in class net.librec.recommender.context.rating.SoRegRecommender
-
predict a specific rating for user userIdx on item itemIdx.
- 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(int, int, SparseVector) - Method in class net.librec.recommender.FactorizationMachineRecommender
-
Predict the rating given a sparse appender vector.
- predict(int, int, 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
- 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
-
- 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.content.HFTRecommender
-
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.content.HFTRecommender
-
item regularization
- 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.content.HFTRecommender
-
user 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.
- reviewMappingData - Variable in class net.librec.recommender.content.HFTRecommender
-
- 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
-
- sampleLag - Variable in class net.librec.recommender.ProbabilisticGraphicalRecommender
-
sample lag (if -1 only one sample taken)
- sampleTopicsToWords(String[], int) - Method in class net.librec.recommender.content.HFTRecommender
-
- 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.ListRankMFRecommender
-
- 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
-
- 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
-
- 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.
- 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
- 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
- trainMatrix - Variable in class net.librec.recommender.content.EFMRecommender
-
- trainMatrix - Variable in class net.librec.recommender.content.HFTRecommender
-
- 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.ListRankMFRecommender
-
- 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
-
The training approach is SGD instead of L-BFGS, so it can be slow if the dataset
is big.
- 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
-
- 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
-
- updateArray(double[], double[]) - Method in class net.librec.recommender.content.HFTRecommender
-
Update function for thetas and phiks, check if softmax comes in to NaN
and update the parameters.
- 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
- userBiases - Variable in class net.librec.recommender.content.HFTRecommender
-
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.ListRankMFRecommender
-
- userFactors - Variable in class net.librec.recommender.content.EFMRecommender
-
user latent factors
- userFactors - Variable in class net.librec.recommender.content.HFTRecommender
-
user latent factors
- 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
- 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
-