Index (CF4J 2.3.0 API Documentation)

A B C D E F G H I J K L M N P Q R S T U V W X Y
All Classes All Packages

A

a - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: User factors
a - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
add(int, double) - Method in class es.upm.etsisi.cf4j.data.types.SortedRatingList: Adds an ordered rating to the SortedRatingList.
addColumn(String, double) - Method in class es.upm.etsisi.cf4j.util.plot.ColumnPlot: Adds a column to the plot
addFixedParam(String, boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.ParamsGrid: Adds a fixed parameter
addFixedParam(String, double) - Method in class es.upm.etsisi.cf4j.util.optimization.ParamsGrid: Adds a fixed parameter
addFixedParam(String, int) - Method in class es.upm.etsisi.cf4j.util.optimization.ParamsGrid: Adds a fixed parameter
addFixedParam(String, long) - Method in class es.upm.etsisi.cf4j.util.optimization.ParamsGrid: Adds a fixed parameter
addFixedParam(String, Object) - Method in class es.upm.etsisi.cf4j.util.optimization.ParamsGrid: Adds a fixed parameter
addFixedParam(String, String) - Method in class es.upm.etsisi.cf4j.util.optimization.ParamsGrid: Adds a fixed parameter
addParam(String, boolean[]) - Method in class es.upm.etsisi.cf4j.util.optimization.ParamsGrid: Adds a variable parameter
addParam(String, double[]) - Method in class es.upm.etsisi.cf4j.util.optimization.ParamsGrid: Adds a variable parameter
addParam(String, int[]) - Method in class es.upm.etsisi.cf4j.util.optimization.ParamsGrid: Adds a variable parameter
addParam(String, long[]) - Method in class es.upm.etsisi.cf4j.util.optimization.ParamsGrid: Adds a variable parameter
addParam(String, Object[]) - Method in class es.upm.etsisi.cf4j.util.optimization.ParamsGrid: Adds a variable parameter
addParam(String, String[]) - Method in class es.upm.etsisi.cf4j.util.optimization.ParamsGrid: Adds a variable parameter
addPoint(double, double) - Method in class es.upm.etsisi.cf4j.util.plot.ScatterPlot: Adds new point to the scatter plot
addRating(int, double) - Method in class es.upm.etsisi.cf4j.data.Item: Adds a new rating of an user to the item.
addRating(int, double) - Method in class es.upm.etsisi.cf4j.data.User: Adds a new rating of the user to an item.
addRating(int, int, double) - Method in class es.upm.etsisi.cf4j.data.DataModel: Adds a single (training) rating to the DataModel.
addSeries(String) - Method in class es.upm.etsisi.cf4j.util.plot.LinePlot: Adds a new empty series to the plot.
addSeries(String) - Method in class es.upm.etsisi.cf4j.util.plot.XYPlot: Adds a new empty series to the plot.
addSeries(String, double) - Method in class es.upm.etsisi.cf4j.util.plot.LinePlot: Adds a new series to the plot initializing all the values to a constant one.
addSeries(String, double[]) - Method in class es.upm.etsisi.cf4j.util.plot.LinePlot: Adds a new series to the plot. y values positions must be correlated with xs values.
addSeries(String, double[], double[]) - Method in class es.upm.etsisi.cf4j.util.plot.XYPlot: Adds a new series to the plot. xs and ys positions must be correlated with point labels.
addSeries(String, double, double) - Method in class es.upm.etsisi.cf4j.util.plot.XYPlot: Adds a new series to the plot initializing x and y to a constant one for all point labels.
addTestRating(int, double) - Method in class es.upm.etsisi.cf4j.data.TestItem: Adds a new test rating of a test user to the test item.
addTestRating(int, double) - Method in class es.upm.etsisi.cf4j.data.TestUser: Adds a new test rating of the test user to an test item.
addTestRating(int, int, double) - Method in class es.upm.etsisi.cf4j.data.DataModel: Adds a single test rating to the DataModel.
addValue(double) - Method in class es.upm.etsisi.cf4j.util.plot.HistogramPlot: Adds new value to the histogram
AdjustedCosine - Class in es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric: Implements traditional Adjusted Cosine as CF similarity metric for the items.
AdjustedCosine - Class in es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric: Implements traditional Adjusted Cosine as CF similarity metric.
AdjustedCosine() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.AdjustedCosine
AdjustedCosine() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.AdjustedCosine
afterRun() - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.ItemSimilarityMetric
afterRun() - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.UserSimilarityMetric
afterRun() - Method in interface es.upm.etsisi.cf4j.util.process.Partible: Is executed once after execute the method exec.
aggregationApproach - Variable in class es.upm.etsisi.cf4j.recommender.knn.ItemKNN: Aggregation approach used to aggregate k-nearest neighbors ratings
aggregationApproach - Variable in class es.upm.etsisi.cf4j.recommender.knn.UserKNN: Aggregation approach used to aggregate k-nearest neighbors ratings
alpha - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: This hyper-parameter is related to the possibility of obtaining overlapping groups of users sharing the same tastes.
alpha - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Alpha parameter
aPrime - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
arrayAverage(double[]) - Static method in class es.upm.etsisi.cf4j.util.Maths: Calculates the average of an double array
arrayAverage(int[]) - Static method in class es.upm.etsisi.cf4j.util.Maths: Calculates the average of an int array
arrayStandardDeviation(double[]) - Static method in class es.upm.etsisi.cf4j.util.Maths: Calculates the standard deviation of an double array
arrayStandardDeviation(int[]) - Static method in class es.upm.etsisi.cf4j.util.Maths: Calculate the standard deviation of an int array
average - Variable in class es.upm.etsisi.cf4j.data.Item: Average (training) rating
average - Variable in class es.upm.etsisi.cf4j.data.User: Average (training) rating
averageTest - Variable in class es.upm.etsisi.cf4j.data.TestItem: Average test rating
averageTest - Variable in class es.upm.etsisi.cf4j.data.TestUser: Average test rating

B

b - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Item factors
beforeRun() - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.ItemSimilarityMetric
beforeRun() - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.JMSD
beforeRun() - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.MSD
beforeRun() - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.PIP
beforeRun() - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.Singularities
beforeRun() - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.CJMSD
beforeRun() - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.JMSD
beforeRun() - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.MSD
beforeRun() - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.PIP
beforeRun() - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.Singularities
beforeRun() - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.UserSimilarityMetric
beforeRun() - Method in interface es.upm.etsisi.cf4j.util.process.Partible: Is executed once before execute the method 'exec'.
BeMF - Class in es.upm.etsisi.cf4j.recommender.matrixFactorization: Implements Ortega, F., Lara-Cabrera, R., González-Prieto, Á., & Bobadilla, J. (2021).
BeMF(DataModel, int, int, double, double, double[]) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.BeMF: Model constructor
BeMF(DataModel, int, int, double, double, double[], long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.BeMF: Model constructor
BeMF(DataModel, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.BeMF: Model constructor from a Map containing the model's hyper-parameters values.
BenchmarkDataModels - Class in es.upm.etsisi.cf4j.data: This class allows final users to work with benchmark DataModel instances.
BenchmarkDataModels() - Constructor for class es.upm.etsisi.cf4j.data.BenchmarkDataModels
beta - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: This hyper-parameter represents the amount of evidence that the algorithm requires to deduce that a group of users likes an item.
beta - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Beta parameter
bi - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Item bias
bi - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: bi parameter
BiasedMF - Class in es.upm.etsisi.cf4j.recommender.matrixFactorization: Implements Koren, Y., Bell, R., & Volinsky, C. (2009).
BiasedMF(DataModel, int, int) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Model constructor
BiasedMF(DataModel, int, int, double) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Model constructor
BiasedMF(DataModel, int, int, double, double, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Model constructor
BiasedMF(DataModel, int, int, double, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Model constructor
BiasedMF(DataModel, int, int, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Model constructor
BiasedMF(DataModel, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Model constructor from a Map containing the model's hyper-parameters values.
BiasedMFGridSearch - Class in es.upm.etsisi.cf4j.examples.gridSearch: In this example we tune the hyper-parameters of BiasedMF recommender using the GridSearch tool.
BiasedMFGridSearch() - Constructor for class es.upm.etsisi.cf4j.examples.gridSearch.BiasedMFGridSearch
BNMF - Class in es.upm.etsisi.cf4j.recommender.matrixFactorization: Implements Hernando, A., Bobadilla, J., & Ortega, F. (2016).
BNMF(DataModel, int, int, double, double) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Model constructor
BNMF(DataModel, int, int, double, double, double, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Model constructor
BNMF(DataModel, int, int, double, double, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Model constructor
BNMF(DataModel, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Model constructor from a Map containing the model's hyper-parameters values.
BoardGameGeek() - Static method in class es.upm.etsisi.cf4j.data.BenchmarkDataModels: Loads a DataModel instance of BoardGameGeek dataset.
BookCrossing() - Static method in class es.upm.etsisi.cf4j.data.BenchmarkDataModels: Loads a DataModel instance of BookCrossing dataset.
bPrime - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
bu - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: User bias
bu - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: bu parameter

C

c - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
CJMSD - Class in es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric: Implements the following CF similarity metric: Bobadilla, J., Ortega, F., Hernando, A., & Arroyo, A. (2012).
CJMSD() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.CJMSD
CLiMF - Class in es.upm.etsisi.cf4j.recommender.matrixFactorization: Implements Shi, Y., Karatzoglou, A., Baltrunas, L., Larson, M., Oliver, N., & Hanjalic, A
CLiMF(DataModel, int, double, double, int, double) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Model constructor
CLiMF(DataModel, int, double, double, int, double, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Model constructor
CLiMF(DataModel, int, int) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Model constructor
CLiMF(DataModel, int, int, double) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Model constructor
CLiMF(DataModel, int, int, double, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Model constructor
CLiMF(DataModel, int, int, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Model constructor
CLiMF(DataModel, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Model constructor from a Map containing the model's hyper-parameters values.
ColumnPlot - Class in es.upm.etsisi.cf4j.util.plot: Implements a column plot.
ColumnPlot(String, String) - Constructor for class es.upm.etsisi.cf4j.util.plot.ColumnPlot: Creates a new ColumnPlot
ColumnPlotExample - Class in es.upm.etsisi.cf4j.examples.plot: In this example we analyze the rating value distribution of MovieLens 1M dataset using a ColumnPlot.
ColumnPlotExample() - Constructor for class es.upm.etsisi.cf4j.examples.plot.ColumnPlotExample
compareTo(Rating) - Method in class es.upm.etsisi.cf4j.data.types.Rating
contains(String) - Method in class es.upm.etsisi.cf4j.data.DataBank: Finds if an element exist inside the DataBank
Correlation - Class in es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric: This class Implements Pearson Correlation as CF similarity metric for the items.
Correlation - Class in es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric: Implements traditional Pearson Correlation as CF similarity metric.
Correlation() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.Correlation
Correlation() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.Correlation
CorrelationConstrained - Class in es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric: This class implements the Constrained Correlation as CF similarity metric for items.
CorrelationConstrained - Class in es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric: Implements traditional Pearson Correlation Constrained as CF similarity metric.
CorrelationConstrained(double) - Constructor for class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.CorrelationConstrained: Constructor of the similarity metric
CorrelationConstrained(double) - Constructor for class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.CorrelationConstrained: Constructor of the similarity metric
Cosine - Class in es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric: Implements Cosine as CF similarity metric for the items.
Cosine - Class in es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric: Implements traditional Cosine as CF similarity metric.
Cosine() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.Cosine
Cosine() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.Cosine
Coverage - Class in es.upm.etsisi.cf4j.qualityMeasure.prediction: This class calculates the Coverage of the recommender system.
Coverage(Recommender) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.prediction.Coverage: Constructor of the class which basically calls the father's one.
cPrime - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF

D

dataBank - Variable in class es.upm.etsisi.cf4j.data.Item: DataBank to store heterogeneous information
dataBank - Variable in class es.upm.etsisi.cf4j.data.User: DataBank to store heterogeneous information
DataBank - Class in es.upm.etsisi.cf4j.data: DataBank is focused on storing heterogeneous data as a support to the calculations made in the recommendation process.
DataBank() - Constructor for class es.upm.etsisi.cf4j.data.DataBank
dataCalculation(TestUser, int[]) - Method in class es.upm.etsisi.cf4j.qualityMeasure.recommendation.NDCG: Function to process de data in the NDCG algorithm.
datamodel - Variable in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.ItemSimilarityMetric: DataModel for which de similarities must be computed
datamodel - Variable in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.UserSimilarityMetric: DataModel for which de similarities must be computed
datamodel - Variable in class es.upm.etsisi.cf4j.recommender.Recommender: DataModel instance used for the Recommender
DataModel - Class in es.upm.etsisi.cf4j.data: This class manages all the information related with a collaborative filtering based recommender system.
DataModel(DataSet) - Constructor for class es.upm.etsisi.cf4j.data.DataModel: This constructor initializes the DataModel with the contents of the given DataSet.
DataSet - Interface in es.upm.etsisi.cf4j.data: This interface works as a bridge between the raw file and the DataModel.
DataSetEntry - Class in es.upm.etsisi.cf4j.data.types: Structural class which stores Triplets: user identifier (String), item identifier (string), and rating value.
DataSetEntry(String, String, double) - Constructor for class es.upm.etsisi.cf4j.data.types.DataSetEntry: Creates a new DataSet entry form an user identifier, an item identifier and a rating value.
DeepMF - Class in es.upm.etsisi.cf4j.recommender.matrixFactorization: Implements Lara-Cabrera, R., González-Prieto, Á., & Ortega, F. (2020).
DeepMF(DataModel, int[], int[], double[], double[]) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.DeepMF: Model constructor
DeepMF(DataModel, int[], int[], double[], double[], long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.DeepMF: Model constructor
DeepMF(DataModel, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.DeepMF: Model constructor from a Map containing the model's hyper-parameters values.
DEFAULT_A - Static variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
DEFAULT_A_PRIME - Static variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
DEFAULT_B_PRIME - Static variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
DEFAULT_C - Static variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
DEFAULT_C_PRIME - Static variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
DEFAULT_D_PRIME - Static variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
DEFAULT_GAMMA - Static variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF
DEFAULT_GAMMA - Static variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF
DEFAULT_GAMMA - Static variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF
DEFAULT_GAMMA - Static variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus
DEFAULT_H - Static variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP
DEFAULT_LAMBDA - Static variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF
DEFAULT_LAMBDA - Static variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF
DEFAULT_LAMBDA - Static variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF
DEFAULT_LAMBDA - Static variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus
DEFAULT_R - Static variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF
DEFAULT_SEPARATOR - Static variable in class es.upm.etsisi.cf4j.data.RandomSplitDataSet
DEFAULT_SEPARATOR - Static variable in class es.upm.etsisi.cf4j.data.TrainTestFilesDataSet
delete(String) - Method in class es.upm.etsisi.cf4j.data.DataBank: Deletes a value associated to a single element key.
deleteAll() - Method in class es.upm.etsisi.cf4j.data.DataBank: Deletes all content of this DataBank.
DEVIATION_FROM_MEAN - es.upm.etsisi.cf4j.recommender.knn.UserKNN.AggregationApproach
DirMF - Class in es.upm.etsisi.cf4j.recommender.matrixFactorization: Implements Lara-Cabrera, R., González, Á., Ortega, F., & González-Prieto, Á. (2022).
DirMF(DataModel, int, int, double, double, double[]) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.DirMF: Model constructor
DirMF(DataModel, int, int, double, double, double[], long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.DirMF: Model constructor
DirMF(DataModel, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.DirMF: Model constructor from a Map containing the model's hyper-parameters values.
Discovery - Class in es.upm.etsisi.cf4j.qualityMeasure.recommendation: This class the averaged novelty of the recomendations.
Discovery(Recommender, int) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.recommendation.Discovery: Constructor of Novelty
Discovery(Recommender, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.recommendation.Discovery: Constructor from a Map object with the quality measure parameters.
Diversity - Class in es.upm.etsisi.cf4j.qualityMeasure.recommendation: This class the averaged diversity of the recomendations.
Diversity(Recommender, int) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.recommendation.Diversity: Constructor of Diversity
Diversity(Recommender, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.recommendation.Diversity: Constructor from a Map object with the quality measure parameters.
dotProduct(double[], double[]) - Static method in class es.upm.etsisi.cf4j.util.Maths: Dot product between two vectors
dPrime - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
draw() - Method in class es.upm.etsisi.cf4j.util.plot.Plot: Draws the plot into a JFrame

E

EPSILON - Static variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP
epsilonMinus - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Epsilon- parameters
epsilonPlus - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Epsilon+ parameters
equals(Object) - Method in class es.upm.etsisi.cf4j.data.types.DataSetEntry
es.upm.etsisi.cf4j.data - package es.upm.etsisi.cf4j.data: This package contains data classes of CF4J.
es.upm.etsisi.cf4j.data.types - package es.upm.etsisi.cf4j.data.types: This package contains types classes used by data objects of CF4J.
es.upm.etsisi.cf4j.examples - package es.upm.etsisi.cf4j.examples: This package contains examples of CF4J usage.
es.upm.etsisi.cf4j.examples.gridSearch - package es.upm.etsisi.cf4j.examples.gridSearch: This package contains examples showing how to use GridSearch tool of CF4J.
es.upm.etsisi.cf4j.examples.plot - package es.upm.etsisi.cf4j.examples.plot: This package contains examples showing how to plot with CF4J
es.upm.etsisi.cf4j.examples.recommender - package es.upm.etsisi.cf4j.examples.recommender: This package contains examples showing how to compare different Recommenders with CF4J.
es.upm.etsisi.cf4j.qualityMeasure - package es.upm.etsisi.cf4j.qualityMeasure: Contains the implementation of different quality measures for collaborative filtering based recommender systems.
es.upm.etsisi.cf4j.qualityMeasure.prediction - package es.upm.etsisi.cf4j.qualityMeasure.prediction: Contains the implementation of different quality measures oriented to predictions.
es.upm.etsisi.cf4j.qualityMeasure.recommendation - package es.upm.etsisi.cf4j.qualityMeasure.recommendation: Contains the implementation of different quality measures oriented to recommendations.
es.upm.etsisi.cf4j.recommender - package es.upm.etsisi.cf4j.recommender: This package contains the implementation of different collaborative filtering based recommenders.
es.upm.etsisi.cf4j.recommender.knn - package es.upm.etsisi.cf4j.recommender.knn: This package contains the implementation of different knn based collaborative filtering recommenders.
es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric - package es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric: This package contains different implementations of item-to-item similarity metrics used in the item-to-item knn based collaborative filtering algorithm.
es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric - package es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric: This package contains different implementations of user-to-user similarity metric used in the user-to-user knn based collaborative filtering algorithm.
es.upm.etsisi.cf4j.recommender.matrixFactorization - package es.upm.etsisi.cf4j.recommender.matrixFactorization: This package contains the implementation of different matrix factorization based collaborative filtering recommenders.
es.upm.etsisi.cf4j.recommender.neural - package es.upm.etsisi.cf4j.recommender.neural: This package contains the implementation of different neural networks based collaborative filtering recommenders.
es.upm.etsisi.cf4j.util - package es.upm.etsisi.cf4j.util: This package contains different utilities used by the CF4J.
es.upm.etsisi.cf4j.util.optimization - package es.upm.etsisi.cf4j.util.optimization: This package includes optimization utils designed to tune recommenders' hyper-parameters.
es.upm.etsisi.cf4j.util.plot - package es.upm.etsisi.cf4j.util.plot: This package includes plotting utils designed to analyze data of results obtained as consequence of collaborative filtering research.
es.upm.etsisi.cf4j.util.process - package es.upm.etsisi.cf4j.util.process: This package includes processing utils designed to parallelize fitting processes.
exec(Object[], Partible) - Static method in class es.upm.etsisi.cf4j.util.process.Parallelizer: Execs Partible for each object contained in the objects array.
exec(Object[], Partible, int) - Static method in class es.upm.etsisi.cf4j.util.process.Parallelizer: Execs Partible for each object contained in the objects array.
exportData(String) - Method in class es.upm.etsisi.cf4j.util.plot.Plot: Exports plot data into a CSV file
exportData(String, boolean) - Method in class es.upm.etsisi.cf4j.util.plot.Plot: Exports plot data into a CSV file
exportData(String, String) - Method in class es.upm.etsisi.cf4j.util.plot.Plot: Exports plot data into a CSV file
exportData(String, String, boolean) - Method in class es.upm.etsisi.cf4j.util.plot.Plot: Exports plot data into a CSV file
exportPlot(String) - Method in class es.upm.etsisi.cf4j.util.plot.Plot: Exports the plot to a PNG file
exportResults(String) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearch: Exports results of RandomSerach in csv format
exportResults(String) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: Exports results of RandomSerachCV in csv format
exportResults(String, boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearch: Exports results of RandomSerach in csv format
exportResults(String, boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: Exports results of RandomSerachCV in csv format
exportResults(String, String) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearch: Exports results of RandomSerach in csv format
exportResults(String, String) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: Exports results of RandomSerachCV in csv format
exportResults(String, String, boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearch: Exports results of RandomSerach in csv format
exportResults(String, String, boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: Exports results of RandomSerachCV in csv format
exportToCSV(String, String) - Method in class es.upm.etsisi.cf4j.data.DataModel: Exports datamodel into a CSV for train ratings and other CSV for test ratings.
exportToCSV(String, String, boolean) - Method in class es.upm.etsisi.cf4j.data.DataModel: Exports datamodel into a CSV for train ratings and other CSV for test ratings.
exportToCSV(String, String, String) - Method in class es.upm.etsisi.cf4j.data.DataModel: Exports datamodel into a CSV for train ratings and other CSV for test ratings.
exportToCSV(String, String, String, boolean) - Method in class es.upm.etsisi.cf4j.data.DataModel: Exports datamodel into a CSV for train ratings and other CSV for test ratings.

F

F1 - Class in es.upm.etsisi.cf4j.qualityMeasure.recommendation: This class calculates the F1 score of the recommender system.
F1(Recommender, int, double) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.recommendation.F1: Constructor
F1(Recommender, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.recommendation.F1: Constructor from a Map object with the quality measure parameters.
FilmTrust() - Static method in class es.upm.etsisi.cf4j.data.BenchmarkDataModels: Loads a DataModel instance of FilmTrust dataset.
find(int) - Method in class es.upm.etsisi.cf4j.data.types.SortedRatingList: Finds the position of an index
findItem(int) - Method in class es.upm.etsisi.cf4j.data.User: Finds position of a user's rating given the index of the Item in the DataModel.
findItemIndex(String) - Method in class es.upm.etsisi.cf4j.data.DataModel: Finds the itemIndex of an Item at the Items' array given its unique id.
findTestItem(int) - Method in class es.upm.etsisi.cf4j.data.TestUser: Finds position of a user's test rating given the index of the TestItem in the DataModel.
findTestItemIndex(String) - Method in class es.upm.etsisi.cf4j.data.DataModel: Finds the testItemIndex of a TestItem at the TestItem' array given its unique id.
findTestUser(int) - Method in class es.upm.etsisi.cf4j.data.TestItem: Finds position of a rating that an test user has made to the test item given the index of the TestUser in the DataModel.
findTestUserIndex(String) - Method in class es.upm.etsisi.cf4j.data.DataModel: Finds the testUserIndex of a TestUser at the TestUsers' array given his/her unique id.
findTopN(double[], int) - Static method in class es.upm.etsisi.cf4j.util.Search: Returns the indexes of the biggest n elements of the values array.
findUser(int) - Method in class es.upm.etsisi.cf4j.data.Item: Finds position of a rating that an user has made to the item given the index of the User in the DataModel.
findUserIndex(String) - Method in class es.upm.etsisi.cf4j.data.DataModel: Finds the userIndex of a User at the Users' array given his/her unique id.
fit() - Method in class es.upm.etsisi.cf4j.recommender.knn.ItemKNN
fit() - Method in class es.upm.etsisi.cf4j.recommender.knn.UserKNN
fit() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BeMF
fit() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF
fit() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF
fit() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF
fit() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.DeepMF
fit() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.DirMF
fit() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
fit() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.NMF
fit() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF
fit() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus
fit() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP
fit() - Method in class es.upm.etsisi.cf4j.recommender.neural.GMF
fit() - Method in class es.upm.etsisi.cf4j.recommender.neural.MLP
fit() - Method in class es.upm.etsisi.cf4j.recommender.neural.NCCF
fit() - Method in class es.upm.etsisi.cf4j.recommender.neural.NeuMF
fit() - Method in class es.upm.etsisi.cf4j.recommender.Recommender: Estimates model parameters given the hyper-parameters
fit() - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearch: Performs grid search
fit() - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: Performs the search

G

gamma - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Learning rate
gamma - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Gamma parameters
gamma - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Learning rate
gamma - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
gamma - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: Learning rate
gamma - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: Learning rate hyper-parameter
gamma - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Gamma parameter
gammaRte - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
gammaShp - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
getAlpha() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Get the alpha value
getBackgroundColor() - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Gets the plot's background color
getBestParams() - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearch: Get the best result parameters.
getBestParams() - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: Get the best result parameters.
getBestParams(boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearch: Get the best result parameters.
getBestParams(boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: Get the best result parameters.
getBestParams(int, boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearch: Get the best result parameters.
getBestParams(int, boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: Get the best result parameters.
getBestScore() - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearch: Get the best result score.
getBestScore() - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: Get the best result score.
getBestScore(boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearch: Get the best result score.
getBestScore(boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: Get the best result score.
getBestScore(int, boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearch: Get the best result score.
getBestScore(int, boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: Get the best result score.
getBeta() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Get the beta value
getBoolean(String) - Method in class es.upm.etsisi.cf4j.data.DataBank: Gets an stored boolean inside the DataBank.
getBooleanArray(String) - Method in class es.upm.etsisi.cf4j.data.DataBank: Gets an stored boolean array inside the DataBank.
getClearInset() - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Gets the inset for a clear border
getColor(int) - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Gets a color from the palette
getColorPalette() - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Gets the color palette
getDataBank() - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets the DataBank instance that stores heterogeneous information related to the DataModel.
getDataBank() - Method in class es.upm.etsisi.cf4j.data.Item: Gets the DataBank instance that stores heterogeneous information related to the Item.
getDataBank() - Method in class es.upm.etsisi.cf4j.data.User: Gets the DataBank instance that stores heterogeneous information related to the User.
getDataContent(String, String) - Method in class es.upm.etsisi.cf4j.util.plot.ColumnPlot
getDataContent(String, String) - Method in class es.upm.etsisi.cf4j.util.plot.HistogramPlot
getDataContent(String, String) - Method in class es.upm.etsisi.cf4j.util.plot.LinePlot
getDataContent(String, String) - Method in class es.upm.etsisi.cf4j.util.plot.Plot: Returns an String matrix with the content of the plot's data.
getDataContent(String, String) - Method in class es.upm.etsisi.cf4j.util.plot.ScatterPlot
getDataContent(String, String) - Method in class es.upm.etsisi.cf4j.util.plot.XYPlot
getDataHeaders() - Method in class es.upm.etsisi.cf4j.util.plot.ColumnPlot
getDataHeaders() - Method in class es.upm.etsisi.cf4j.util.plot.HistogramPlot
getDataHeaders() - Method in class es.upm.etsisi.cf4j.util.plot.LinePlot
getDataHeaders() - Method in class es.upm.etsisi.cf4j.util.plot.Plot: Returns an String array with the headers of the plot's data
getDataHeaders() - Method in class es.upm.etsisi.cf4j.util.plot.ScatterPlot
getDataHeaders() - Method in class es.upm.etsisi.cf4j.util.plot.XYPlot
getDataModel() - Method in class es.upm.etsisi.cf4j.recommender.Recommender: Returns the DataModel instance
getDevelopmentSetIterator() - Method in class es.upm.etsisi.cf4j.util.optimization.ParamsGrid: Returns the development set created from the grid parameters
getDevelopmentSetIterator(boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.ParamsGrid: Returns the development set created from the grid parameters
getDevelopmentSetIterator(boolean, long) - Method in class es.upm.etsisi.cf4j.util.optimization.ParamsGrid: Returns the development set created from the grid parameters
getDevelopmentSetSize() - Method in class es.upm.etsisi.cf4j.util.optimization.ParamsGrid
getDouble(String) - Method in class es.upm.etsisi.cf4j.data.DataBank: Gets an stored double inside the DataBank.
getDoubleArray(String) - Method in class es.upm.etsisi.cf4j.data.DataBank: Gets an stored double array inside the DataBank.
getEpsilonMinus(int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Get the epsilon- vector of an item
getEpsilonPlus(int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Get the epsilon+ vector of an item
getGamma() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Get the learning rate parameter of the model
getGamma() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Get the learning rate parameter of the model
getGamma() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: Get the learning rate parameter of the model
getGamma() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: Getter of the gamma value.
getGamma(int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Get the gamma vector of an user
getGMFNumFactors() - Method in class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Returns the number of latent factors of GMF net.
getGralPlot() - Method in class es.upm.etsisi.cf4j.util.plot.ColumnPlot
getGralPlot() - Method in class es.upm.etsisi.cf4j.util.plot.HistogramPlot
getGralPlot() - Method in class es.upm.etsisi.cf4j.util.plot.LinePlot
getGralPlot() - Method in class es.upm.etsisi.cf4j.util.plot.Plot: Gets an AbstractPlot using GRAL
getGralPlot() - Method in class es.upm.etsisi.cf4j.util.plot.ScatterPlot
getGralPlot() - Method in class es.upm.etsisi.cf4j.util.plot.XYPlot
getH() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Get the H value
getHeight() - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Get the plot height in pixels
getId() - Method in class es.upm.etsisi.cf4j.data.Item: Returns the item unique identifier
getId() - Method in class es.upm.etsisi.cf4j.data.User: Returns the user unique identifier
getIndex() - Method in class es.upm.etsisi.cf4j.data.types.Rating: Gets the stored index.
getIndex(int[], int) - Static method in class es.upm.etsisi.cf4j.util.Search: Gets efficiently the userIndex of an element in an array of integers
getInt(String) - Method in class es.upm.etsisi.cf4j.data.DataBank: Gets an stored int inside the DataBank.
getIntArray(String) - Method in class es.upm.etsisi.cf4j.data.DataBank: Gets an stored int array inside the DataBank.
getItem(int) - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets an Item by its index.
getItemAt(int) - Method in class es.upm.etsisi.cf4j.data.User: Returns the index of the Item rated by the User at the given position.
getItemBias(int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Get the bias of a item (bi)
getItemFactors(int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Get the latent factors vector of an item (qi)
getItemFactors(int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Get the latent factors vector of an item (bi)
getItemFactors(int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: Get the latent factors vector of an item (qi)
getItemIndex() - Method in class es.upm.etsisi.cf4j.data.Item: Return the item index inside the DataModel
getItems() - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets the array of Items.
getLabelsFont() - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Gets the labels font
getLambda() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Get the regularization parameter of the model
getLambda() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Get the regularization parameter of the model
getLambda() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: Get the regularization parameter of the model
getLambda() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: Getter of the Lambda value.
getLayers() - Method in class es.upm.etsisi.cf4j.recommender.neural.MLP: Returns net layers.
getLayers() - Method in class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Returns net layers.
getLearningRate() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BeMF: Get the learning rate parameter of the model
getLearningRate() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.DirMF: Get the learning rate parameter of the model
getLearningRate() - Method in class es.upm.etsisi.cf4j.recommender.neural.GMF: Returns learning rate.
getLearningRate() - Method in class es.upm.etsisi.cf4j.recommender.neural.MLP: Returns learning rate.
getLearningRate() - Method in class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Returns learning rate.
getLegendDistance() - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Gets the legend distance
getLegendFont() - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Gets the legend font
getLegendInset() - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Gets the inset for the legend
getMaxRating() - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets the maximum (training) rating.
getMaxRating() - Method in class es.upm.etsisi.cf4j.data.Item: Gets the maximum rating received by the item.
getMaxRating() - Method in class es.upm.etsisi.cf4j.data.User: Gets the maximum rating of the user
getMaxTestRating() - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets the maximum test rating.
getMaxTestRating() - Method in class es.upm.etsisi.cf4j.data.TestItem: Gets the maximum test rating received by the item
getMaxTestRating() - Method in class es.upm.etsisi.cf4j.data.TestUser: Gets the maximum test rating of the user
getMinRating() - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets the minimum (training) rating.
getMinRating() - Method in class es.upm.etsisi.cf4j.data.Item: Gets the minimum rating received by the item.
getMinRating() - Method in class es.upm.etsisi.cf4j.data.User: Gets the minimum rating of the user
getMinTestRating() - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets the minimum test rating.
getMinTestRating() - Method in class es.upm.etsisi.cf4j.data.TestItem: Gets the minimum test rating received by the item
getMinTestRating() - Method in class es.upm.etsisi.cf4j.data.TestUser: Gets the minimum test rating of the user
getMLPNumFactors() - Method in class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Returns the number of latent factors of MLP net.
getNumberOfItems() - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets the number of items contained in the DataModel.
getNumberOfRatings() - Method in class es.upm.etsisi.cf4j.data.DataModel: Return the number of ratings contained in the DataModel.
getNumberOfRatings() - Method in interface es.upm.etsisi.cf4j.data.DataSet: This method indicates the number of (training) ratings.
getNumberOfRatings() - Method in class es.upm.etsisi.cf4j.data.Item: Gets the number of ratings that the item have received
getNumberOfRatings() - Method in class es.upm.etsisi.cf4j.data.ManualDataSet
getNumberOfRatings() - Method in class es.upm.etsisi.cf4j.data.RandomSplitDataSet
getNumberOfRatings() - Method in class es.upm.etsisi.cf4j.data.TrainTestFilesDataSet
getNumberOfRatings() - Method in class es.upm.etsisi.cf4j.data.User: Gets the number of items rated by the user
getNumberOfTestItems() - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets the number of test items contained in the DataModel.
getNumberOfTestRatings() - Method in class es.upm.etsisi.cf4j.data.DataModel: Return the number of test ratings contained in the DataModel.
getNumberOfTestRatings() - Method in interface es.upm.etsisi.cf4j.data.DataSet: This method indicates the number of test ratings.
getNumberOfTestRatings() - Method in class es.upm.etsisi.cf4j.data.ManualDataSet
getNumberOfTestRatings() - Method in class es.upm.etsisi.cf4j.data.RandomSplitDataSet
getNumberOfTestRatings() - Method in class es.upm.etsisi.cf4j.data.TestItem: Gets the number of test users that have rated the item.
getNumberOfTestRatings() - Method in class es.upm.etsisi.cf4j.data.TestUser: Gets the number of test items rated by the user.
getNumberOfTestRatings() - Method in class es.upm.etsisi.cf4j.data.TrainTestFilesDataSet
getNumberOfTestUsers() - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets the number of test users contained in the DataModel.
getNumberOfUsers() - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets the number of users contained in the DataModel.
getNumEpochs() - Method in class es.upm.etsisi.cf4j.recommender.neural.GMF: Returns the number of epochs.
getNumEpochs() - Method in class es.upm.etsisi.cf4j.recommender.neural.MLP: Returns the number of epochs.
getNumEpochs() - Method in class es.upm.etsisi.cf4j.recommender.neural.NCCF: Returns the number of epochs.
getNumEpochs() - Method in class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Returns the number of epochs.
getNumFactors() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BeMF: Get the number of factors of the model
getNumFactors() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Get the number of factors of the model
getNumFactors() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Get the number of factors of the model
getNumFactors() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Get the number of factors of the model
getNumFactors() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.DirMF: Get the number of factors of the model
getNumFactors() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF: Get the number of factors of the model
getNumFactors() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.NMF: Get the number of factors of the model
getNumFactors() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: Get the number of factors of the model
getNumFactors() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: Number of factors used in this recommender.
getNumFactors() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Get the number of factors of the model
getNumFactors() - Method in class es.upm.etsisi.cf4j.recommender.neural.GMF: Returns the number of latent factors.
getNumFactors() - Method in class es.upm.etsisi.cf4j.recommender.neural.MLP: Returns the number of latent factors.
getNumIters() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BeMF: Get the number of iterations
getNumIters() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Get the number of iterations
getNumIters() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Get the number of iterations
getNumIters() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Get the number of iterations
getNumIters() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.DirMF: Get the number of iterations
getNumIters() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF: Get the number of iterations
getNumIters() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.NMF: Get the number of iterations
getNumIters() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: Get the number of iterations
getNumIters() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: Number of iterations used in this recommender.
getNumIters() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Get the number of iterations
getParamsName() - Method in class es.upm.etsisi.cf4j.util.optimization.ParamsGrid: Returns String Array with the name of the params
getPointsFont() - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Gets the points font
getPredictionProbabilityDistribution(int, int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Returns the probability distribution of a prediction.
getR() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Get the r value
getRating() - Method in class es.upm.etsisi.cf4j.data.types.Rating: Gets the rating value.
getRatingAt(int) - Method in class es.upm.etsisi.cf4j.data.Item: Returns the rating of the user to the item at the pos position
getRatingAt(int) - Method in class es.upm.etsisi.cf4j.data.User: Returns the rating of the user to the item at the pos position
getRatingAverage() - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets the average of (training) ratings.
getRatingAverage() - Method in class es.upm.etsisi.cf4j.data.Item: Gets the average value of ratings
getRatingAverage() - Method in class es.upm.etsisi.cf4j.data.User: Gets the average value of ratings
getRatings() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BeMF: Get the discrete ratings values
getRatings() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.DirMF: Get the discrete ratings values
getRatings() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Get the plausible ratings
getRatingsIterator() - Method in interface es.upm.etsisi.cf4j.data.DataSet: This method generates an iterator to navigate through the raw ratings stored in DataSetEntries.
getRatingsIterator() - Method in class es.upm.etsisi.cf4j.data.ManualDataSet
getRatingsIterator() - Method in class es.upm.etsisi.cf4j.data.RandomSplitDataSet
getRatingsIterator() - Method in class es.upm.etsisi.cf4j.data.TrainTestFilesDataSet
getRegularization() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BeMF: Get the regularization parameter of the model
getRegularization() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.DirMF: Get the regularization parameter of the model
getResults() - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearch: This method is required for cross validation (CV).
getScore() - Method in class es.upm.etsisi.cf4j.qualityMeasure.QualityMeasure: Computes the quality measure of the recommender
getScore(int) - Method in class es.upm.etsisi.cf4j.qualityMeasure.QualityMeasure: Computes the quality measure of the recommender
getScore(TestUser, double[]) - Method in class es.upm.etsisi.cf4j.qualityMeasure.prediction.Coverage
getScore(TestUser, double[]) - Method in class es.upm.etsisi.cf4j.qualityMeasure.prediction.MAE
getScore(TestUser, double[]) - Method in class es.upm.etsisi.cf4j.qualityMeasure.prediction.Max
getScore(TestUser, double[]) - Method in class es.upm.etsisi.cf4j.qualityMeasure.prediction.MSE
getScore(TestUser, double[]) - Method in class es.upm.etsisi.cf4j.qualityMeasure.prediction.MSLE
getScore(TestUser, double[]) - Method in class es.upm.etsisi.cf4j.qualityMeasure.prediction.Perfect
getScore(TestUser, double[]) - Method in class es.upm.etsisi.cf4j.qualityMeasure.prediction.R2
getScore(TestUser, double[]) - Method in class es.upm.etsisi.cf4j.qualityMeasure.prediction.RMSE
getScore(TestUser, double[]) - Method in class es.upm.etsisi.cf4j.qualityMeasure.QualityMeasure: Computes the quality measure score for a TestUser given the predictions for his/her test ratings
getScore(TestUser, double[]) - Method in class es.upm.etsisi.cf4j.qualityMeasure.recommendation.Discovery
getScore(TestUser, double[]) - Method in class es.upm.etsisi.cf4j.qualityMeasure.recommendation.Diversity
getScore(TestUser, double[]) - Method in class es.upm.etsisi.cf4j.qualityMeasure.recommendation.F1
getScore(TestUser, double[]) - Method in class es.upm.etsisi.cf4j.qualityMeasure.recommendation.NDCG
getScore(TestUser, double[]) - Method in class es.upm.etsisi.cf4j.qualityMeasure.recommendation.Novelty
getScore(TestUser, double[]) - Method in class es.upm.etsisi.cf4j.qualityMeasure.recommendation.Precision
getScore(TestUser, double[]) - Method in class es.upm.etsisi.cf4j.qualityMeasure.recommendation.Recall
getSimilarities(int) - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.ItemSimilarityMetric: Returns the similarity array of an item.
getSimilarities(int) - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.UserSimilarityMetric: Returns the similarity array of an user.
getString(String) - Method in class es.upm.etsisi.cf4j.data.DataBank: Gets an stored String inside the DataBank.
getStringArray(String) - Method in class es.upm.etsisi.cf4j.data.DataBank: Gets an stored String array inside the DataBank.
getTestItem(int) - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets a TestItem by its index.
getTestItemAt(int) - Method in class es.upm.etsisi.cf4j.data.TestUser: Returns the index of the TestItem rated by the TestUser at the given position.
getTestItemIndex() - Method in class es.upm.etsisi.cf4j.data.TestItem: Returns the test item index inside the DataModel
getTestItems() - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets the array of TestItems.
getTestRatingAt(int) - Method in class es.upm.etsisi.cf4j.data.TestItem: Returns the test rating of the test user to the test item at the pos position
getTestRatingAt(int) - Method in class es.upm.etsisi.cf4j.data.TestUser: Returns the test rating of the user to the test item at the pos position
getTestRatingAverage() - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets the average of test ratings.
getTestRatingAverage() - Method in class es.upm.etsisi.cf4j.data.TestItem: Gets the average value of test ratings
getTestRatingAverage() - Method in class es.upm.etsisi.cf4j.data.TestUser: Gets the average value of test ratings
getTestRatingsIterator() - Method in interface es.upm.etsisi.cf4j.data.DataSet: This method generates an iterator to navigate through the raw test ratings stored in DataSetEntries.
getTestRatingsIterator() - Method in class es.upm.etsisi.cf4j.data.ManualDataSet
getTestRatingsIterator() - Method in class es.upm.etsisi.cf4j.data.RandomSplitDataSet
getTestRatingsIterator() - Method in class es.upm.etsisi.cf4j.data.TrainTestFilesDataSet
getTestUser(int) - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets a TestUser by his/her test index.
getTestUserAt(int) - Method in class es.upm.etsisi.cf4j.data.TestItem: Returns the index of the TestUser that have test rated the TestItem at the given position
getTestUserIndex() - Method in class es.upm.etsisi.cf4j.data.TestUser: Returns the test user index inside the DataModel
getTestUsers() - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets the array of TestUsers.
getTicksFont() - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Gets the ticks font
GettingStartedExample - Class in es.upm.etsisi.cf4j.examples: In this example we analyze how the Mean Squared Error (MSE) varies according to the value of the regularization term in Probabilistic Matrix Factorization (PMF).
GettingStartedExample() - Constructor for class es.upm.etsisi.cf4j.examples.GettingStartedExample
getUser(int) - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets an User by his/her index.
getUserAt(int) - Method in class es.upm.etsisi.cf4j.data.Item: Returns the index of the User that have rated the Item at the given position
getUserBias(int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Get the bias of a user (bu)
getUserFactors(int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Get the latent factors vector of a user (pu)
getUserFactors(int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Get the latent factors vector of a user (au)
getUserFactors(int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: Get the latent factors vector of a user (pu)
getUserIndex() - Method in class es.upm.etsisi.cf4j.data.User: Return the user index inside the DataModel
getUsers() - Method in class es.upm.etsisi.cf4j.data.DataModel: Gets the array of Users.
getWidth() - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Get plot with in pixels
getxAxisInset() - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Gets the inset for the x axis
getxAxisLabelDistance() - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Gets the label distance in the x axis
getyAxisInset() - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Gets the inset for the y axis
getyAxisLabelDistance() - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Gets the label distance in the y axis
GMF - Class in es.upm.etsisi.cf4j.recommender.neural: Implements He, X., Liao, L., Zhang, H., Nie, L., Hu, X., & Chua, T.
GMF(DataModel, int, int, double) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.GMF: Model constructor
GMF(DataModel, int, int, double, long) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.GMF: Model constructor
GMF(DataModel, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.GMF: Model constructor from a Map containing the model's hyper-parameters values.
GridSearch - Class in es.upm.etsisi.cf4j.util.optimization: Utility class to performs a grid search over a Recommender instance.
GridSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>) - Constructor for class es.upm.etsisi.cf4j.util.optimization.GridSearch: GridSearch constructor
GridSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[]) - Constructor for class es.upm.etsisi.cf4j.util.optimization.GridSearch: GridSearch constructor
GridSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], Map<String, Object>[]) - Constructor for class es.upm.etsisi.cf4j.util.optimization.GridSearch: GridSearch constructor
GridSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.util.optimization.GridSearch: GridSearch constructor
GridSearchCV - Class in es.upm.etsisi.cf4j.util.optimization: Utility class to performs a grid search over a Recommender instance.
GridSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], int) - Constructor for class es.upm.etsisi.cf4j.util.optimization.GridSearchCV: GridSearchCV constructor
GridSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], int, long) - Constructor for class es.upm.etsisi.cf4j.util.optimization.GridSearchCV: GridSearchCV constructor
GridSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], Map<String, Object>[], int) - Constructor for class es.upm.etsisi.cf4j.util.optimization.GridSearchCV: GridSearchCV constructor
GridSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], Map<String, Object>[], int, long) - Constructor for class es.upm.etsisi.cf4j.util.optimization.GridSearchCV: GridSearchCV constructor
GridSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, int) - Constructor for class es.upm.etsisi.cf4j.util.optimization.GridSearchCV: GridSearchCV constructor
GridSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, int, long) - Constructor for class es.upm.etsisi.cf4j.util.optimization.GridSearchCV: GridSearchCV constructor
GridSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, Map<String, Object>, int) - Constructor for class es.upm.etsisi.cf4j.util.optimization.GridSearchCV: GridSearchCV constructor
GridSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, Map<String, Object>, int, long) - Constructor for class es.upm.etsisi.cf4j.util.optimization.GridSearchCV: GridSearchCV constructor

H

h - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.NMF: Item factors
H - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Heuristic factor to control number of iterations during E-Step
hashCode() - Method in class es.upm.etsisi.cf4j.data.types.DataSetEntry
HistogramPlot - Class in es.upm.etsisi.cf4j.util.plot: Implements a histogram plot.
HistogramPlot(String, int) - Constructor for class es.upm.etsisi.cf4j.util.plot.HistogramPlot: Creates a new HistogramPlot
HistogramPlotExample - Class in es.upm.etsisi.cf4j.examples.plot: In this example we analyze the average rating of each item that belongs to MovieLens 1M dataset.
HistogramPlotExample() - Constructor for class es.upm.etsisi.cf4j.examples.plot.HistogramPlotExample
HPF - Class in es.upm.etsisi.cf4j.recommender.matrixFactorization: Implements Gopalan, P., Hofman, J.
HPF(DataModel, int, int) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF: Models constructor
HPF(DataModel, int, int, double, double, double, double, double, double) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF: Models constructor
HPF(DataModel, int, int, double, double, double, double, double, double, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF: Models constructor
HPF(DataModel, int, int, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF: Models constructor
HPF(DataModel, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF: Model constructor from a Map containing the model's hyper-parameters values.

I

id - Variable in class es.upm.etsisi.cf4j.data.Item: Item unique identifier
id - Variable in class es.upm.etsisi.cf4j.data.User: User unique identifier
Item - Class in es.upm.etsisi.cf4j.data: Defines a composition of an Item.
Item(String, int) - Constructor for class es.upm.etsisi.cf4j.data.Item: Creates a new instance of an item.
itemId - Variable in class es.upm.etsisi.cf4j.data.types.DataSetEntry: Identifier of the item rated by the user
itemIndex - Variable in class es.upm.etsisi.cf4j.data.Item: Item index in the DataModel
ItemKNN - Class in es.upm.etsisi.cf4j.recommender.knn: Implements item-to-item KNN based collaborative filtering
ItemKNN(DataModel, int, ItemSimilarityMetric, ItemKNN.AggregationApproach) - Constructor for class es.upm.etsisi.cf4j.recommender.knn.ItemKNN: Recommender constructor
ItemKNN(DataModel, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.recommender.knn.ItemKNN: Recommender constructor from a Map containing the recommender's hyper-parameters values.
ItemKNN.AggregationApproach - Enum in es.upm.etsisi.cf4j.recommender.knn: Available aggregation approaches to merge k-nearest neighbors ratings
ItemKnnComparison - Class in es.upm.etsisi.cf4j.examples.recommender: In this example we compare the MSLE and nDCG quality measures scores for different similarity metrics applied to item-to-item knn based collaborative filtering.
ItemKnnComparison() - Constructor for class es.upm.etsisi.cf4j.examples.recommender.ItemKnnComparison
ItemSimilarityMetric - Class in es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric: This class process the similarity measure between two items.
ItemSimilarityMetric() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.ItemSimilarityMetric
itemsRatings - Variable in class es.upm.etsisi.cf4j.data.User: Items rated by the user

J

Jaccard - Class in es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric: This class Implements Jaccard Index as CF similarity metric for the items.
Jaccard - Class in es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric: Implements traditional Jaccard Index as CF similarity metric.
Jaccard() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.Jaccard
Jaccard() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.Jaccard
Jester() - Static method in class es.upm.etsisi.cf4j.data.BenchmarkDataModels: Loads a DataModel instance of Jester (Dataset 3) dataset.
JMSD - Class in es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric: This class implements JMSD as the similarity metric for the items.
JMSD - Class in es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric: Implements the following CF similarity metric: Bobadilla, J., Serradilla, F., & Bernal, J
JMSD() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.JMSD
JMSD() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.JMSD

K

kappaRte - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
kappaShp - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF

L

lambda - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Regularization parameter
lambda - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Regularization
lambda - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
lambda - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: Regularization parameter
lambda - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: Regularization hyper-parameter
lambdaRte - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
lambdaShp - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
layers - Variable in class es.upm.etsisi.cf4j.recommender.neural.MLP: Array of layers neurons
layers - Variable in class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Array of layers neurons
learningRate - Variable in class es.upm.etsisi.cf4j.recommender.neural.GMF: Learning Rate
learningRate - Variable in class es.upm.etsisi.cf4j.recommender.neural.MLP: Learning rate
learningRate - Variable in class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Learning Rate
LibimSeTi() - Static method in class es.upm.etsisi.cf4j.data.BenchmarkDataModels: Loads a DataModel instance of LibimSeTi dataset.
LinePlot - Class in es.upm.etsisi.cf4j.util.plot: Implements a LinePlot.
LinePlot(double[], String, String) - Constructor for class es.upm.etsisi.cf4j.util.plot.LinePlot: Creates a new LinePlot
LinePlot(double[], String, String, boolean) - Constructor for class es.upm.etsisi.cf4j.util.plot.LinePlot: Creates a new LinePlot
LinePlot(int[], String, String) - Constructor for class es.upm.etsisi.cf4j.util.plot.LinePlot: Creates a new LinePlot
LinePlot(int[], String, String, boolean) - Constructor for class es.upm.etsisi.cf4j.util.plot.LinePlot: Creates a new LinePlot
LinePlotExample - Class in es.upm.etsisi.cf4j.examples.plot: In this example we compare the F1 score of the recommendations performed by PMF and NMF recommenders.
LinePlotExample() - Constructor for class es.upm.etsisi.cf4j.examples.plot.LinePlotExample
linespace(double, double, int) - Static method in class es.upm.etsisi.cf4j.util.Maths: Returns num evenly spaced samples.
linespace(double, double, int, boolean) - Static method in class es.upm.etsisi.cf4j.util.Maths: Returns num evenly spaced samples.
linespace(double, int) - Static method in class es.upm.etsisi.cf4j.util.Maths: Returns num evenly spaced samples.
load(String) - Static method in class es.upm.etsisi.cf4j.data.DataModel: Loads a DataModel from a previously serialized file (see save() method).
log(double, double) - Static method in class es.upm.etsisi.cf4j.util.Maths: Returns the log in an specific base
logistic(double) - Static method in class es.upm.etsisi.cf4j.util.Maths: Returns the logistic function g(x)
logspace(double, double, int) - Static method in class es.upm.etsisi.cf4j.util.Maths: Return numbers spaced evenly on a log scale.
logspace(double, double, int, boolean) - Static method in class es.upm.etsisi.cf4j.util.Maths: Return numbers spaced evenly on a log scale.
logspace(double, double, int, boolean, double) - Static method in class es.upm.etsisi.cf4j.util.Maths: Return numbers spaced evenly on a log scale.
logspace(double, double, int, double) - Static method in class es.upm.etsisi.cf4j.util.Maths: Return numbers spaced evenly on a log scale.

M

MAE - Class in es.upm.etsisi.cf4j.qualityMeasure.prediction: This class calculates the Mean Absolute Error (MAE) between the predictions and the test ratings.
MAE(Recommender) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.prediction.MAE: Constructor of the class which basically calls the father's one
main(String[]) - Static method in class es.upm.etsisi.cf4j.examples.GettingStartedExample
main(String[]) - Static method in class es.upm.etsisi.cf4j.examples.gridSearch.BiasedMFGridSearch
main(String[]) - Static method in class es.upm.etsisi.cf4j.examples.gridSearch.PMFRandomSearchCV
main(String[]) - Static method in class es.upm.etsisi.cf4j.examples.gridSearch.UserKNNGridSearch
main(String[]) - Static method in class es.upm.etsisi.cf4j.examples.plot.ColumnPlotExample
main(String[]) - Static method in class es.upm.etsisi.cf4j.examples.plot.HistogramPlotExample
main(String[]) - Static method in class es.upm.etsisi.cf4j.examples.plot.LinePlotExample
main(String[]) - Static method in class es.upm.etsisi.cf4j.examples.plot.ScatterPlotExample
main(String[]) - Static method in class es.upm.etsisi.cf4j.examples.plot.XYPlotExample
main(String[]) - Static method in class es.upm.etsisi.cf4j.examples.recommender.ItemKnnComparison
main(String[]) - Static method in class es.upm.etsisi.cf4j.examples.recommender.MatrixFactorizationComparison
main(String[]) - Static method in class es.upm.etsisi.cf4j.examples.recommender.UserKnnComparison
ManualDataSet - Class in es.upm.etsisi.cf4j.data
ManualDataSet(List<DataSetEntry>, double, Long) - Constructor for class es.upm.etsisi.cf4j.data.ManualDataSet: Method separates the given data set entries into train and test rating depending on the trainPercentage.
ManualDataSet(List<DataSetEntry>, List<DataSetEntry>) - Constructor for class es.upm.etsisi.cf4j.data.ManualDataSet: Method to specify the train and test entries.
Maths - Class in es.upm.etsisi.cf4j.util: This class contains useful math methods.
Maths() - Constructor for class es.upm.etsisi.cf4j.util.Maths
MatrixFactorizationComparison - Class in es.upm.etsisi.cf4j.examples.recommender: In this example we compare the RMSE score for different matrix factorization models varying the number of latent factors.
MatrixFactorizationComparison() - Constructor for class es.upm.etsisi.cf4j.examples.recommender.MatrixFactorizationComparison
max - Variable in class es.upm.etsisi.cf4j.data.Item: Maximum (training) rating value
max - Variable in class es.upm.etsisi.cf4j.data.User: Maximum (training) rating value
Max - Class in es.upm.etsisi.cf4j.qualityMeasure.prediction: This class calculates the averaged maximum prediction absolute error in a the prediction of a test rating for each test user.
Max(Recommender) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.prediction.Max: Constructor of the class which basically calls the father's one.
maxTest - Variable in class es.upm.etsisi.cf4j.data.TestItem: Maximum test rating value
maxTest - Variable in class es.upm.etsisi.cf4j.data.TestUser: Maximum test rating value
MEAN - es.upm.etsisi.cf4j.recommender.knn.ItemKNN.AggregationApproach
MEAN - es.upm.etsisi.cf4j.recommender.knn.UserKNN.AggregationApproach
metric - Variable in class es.upm.etsisi.cf4j.recommender.knn.ItemKNN: Similarity metric to compute the similarity between two items
metric - Variable in class es.upm.etsisi.cf4j.recommender.knn.UserKNN: Similarity metric to compute the similarity between two users
min - Variable in class es.upm.etsisi.cf4j.data.Item: Minimum (training) rating value
min - Variable in class es.upm.etsisi.cf4j.data.User: Minimum (training) rating value
minTest - Variable in class es.upm.etsisi.cf4j.data.TestItem: Minimum test rating value
minTest - Variable in class es.upm.etsisi.cf4j.data.TestUser: Minimum test rating value
MLP - Class in es.upm.etsisi.cf4j.recommender.neural: Implements He, X., Liao, L., Zhang, H., Nie, L., Hu, X., & Chua, T.
MLP(DataModel, int, double) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.MLP: Model constructor
MLP(DataModel, int, double, int[]) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.MLP: Model constructor
MLP(DataModel, int, double, long) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.MLP: Model constructor
MLP(DataModel, int, int, double) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.MLP: Model constructor
MLP(DataModel, int, int, double, int[]) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.MLP: Model constructor
MLP(DataModel, int, int, double, int[], long) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.MLP: Model constructor
MLP(DataModel, int, int, double, long) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.MLP: Model constructor
MLP(DataModel, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.MLP: Model constructor from a Map containing the model's hyper-parameters values.
MovieLens100K() - Static method in class es.upm.etsisi.cf4j.data.BenchmarkDataModels: Loads a DataModel instance of MovieLens 100K dataset.
MovieLens10M() - Static method in class es.upm.etsisi.cf4j.data.BenchmarkDataModels: Loads a DataModel instance of MovieLens 1M dataset.
MovieLens1M() - Static method in class es.upm.etsisi.cf4j.data.BenchmarkDataModels: Loads a DataModel instance of MovieLens 1M dataset.
MSD - Class in es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric: Implements traditional MSD as CF similarity metric for items.
MSD - Class in es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric: Implements traditional MSD as CF similarity metric.
MSD() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.MSD
MSD() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.MSD
MSE - Class in es.upm.etsisi.cf4j.qualityMeasure.prediction: This class calculates the Mean Squared Error (MSE) between the predictions and the test ratings.
MSE(Recommender) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.prediction.MSE: Constructor of the class which basically calls the father's one
MSLE - Class in es.upm.etsisi.cf4j.qualityMeasure.prediction: This class calculates the Mean Squared Logarithmic Error (MSLE) between the predictions and the test ratings.
MSLE(Recommender) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.prediction.MSLE: Constructor of the class which basically calls the father's one
MyAnimeList() - Static method in class es.upm.etsisi.cf4j.data.BenchmarkDataModels: Loads a DataModel instance of MyAnimeList dataset.

N

NCCF - Class in es.upm.etsisi.cf4j.recommender.neural: Implements short method of Bobadilla, J., Ortega, F., Gutiérrez, A., & Alonso, S. (2020).
NCCF(DataModel, int) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.NCCF: Model constructor
NCCF(DataModel, int, long) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.NCCF: Model constructor
NCCF(DataModel, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.NCCF: Model constructor from a Map containing the model's hyper-parameters values.
NDCG - Class in es.upm.etsisi.cf4j.qualityMeasure.recommendation: This class calculates the Normalized Discounted Cumulative Gain (nDCG) of the recommendations performed by a Recommender.
NDCG(Recommender, int) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.recommendation.NDCG: Constructor
NDCG(Recommender, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.recommendation.NDCG: Constructor from a Map object with the quality measure parameters.
neighbors - Variable in class es.upm.etsisi.cf4j.recommender.knn.ItemKNN: Contains the neighbors indexes of each item
neighbors - Variable in class es.upm.etsisi.cf4j.recommender.knn.UserKNN: Contains the neighbors indexes of each user
NetflixPrize() - Static method in class es.upm.etsisi.cf4j.data.BenchmarkDataModels: Loads a DataModel instance of Netflix Prize dataset.
NeuMF - Class in es.upm.etsisi.cf4j.recommender.neural: Implements He, X., Liao, L., Zhang, H., Nie, L., Hu, X., & Chua, T.
NeuMF(DataModel, int, double) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Model constructor
NeuMF(DataModel, int, double, int[]) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Model constructor
NeuMF(DataModel, int, double, long) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Model constructor
NeuMF(DataModel, int, int, int, double) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Model constructor
NeuMF(DataModel, int, int, int, double, int[]) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Model constructor
NeuMF(DataModel, int, int, int, double, int[], long) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Model constructor
NeuMF(DataModel, int, int, int, double, long) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Model constructor
NeuMF(DataModel, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Model constructor from a Map containing the model's hyper-parameters values.
NMF - Class in es.upm.etsisi.cf4j.recommender.matrixFactorization: Implements Lee, D.
NMF(DataModel, int, int) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.NMF: Model constructor
NMF(DataModel, int, int, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.NMF: Model constructor
NMF(DataModel, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.NMF: Model constructor from a Map containing the model's hyper-parameters values.
Novelty - Class in es.upm.etsisi.cf4j.qualityMeasure.recommendation: This class the averaged novelty of the recomendations.
Novelty(Recommender, int) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.recommendation.Novelty: Constructor of Novelty
Novelty(Recommender, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.recommendation.Novelty: Constructor from a Map object with the quality measure parameters.
numberOfNeighbors - Variable in class es.upm.etsisi.cf4j.recommender.knn.ItemKNN: Number of neighbors (k)
numberOfNeighbors - Variable in class es.upm.etsisi.cf4j.recommender.knn.UserKNN: Number of neighbors (k)
numFactors - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Number of latent factors
numFactors - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Number of factors
numFactors - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Number of latent factors
numFactors - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF: Number of latent factors
numFactors - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.NMF: Number of factors
numFactors - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: Number of latent factors
numFactors - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: Number of latent factors
numFactors - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Number of latent factors
numFactors - Variable in class es.upm.etsisi.cf4j.recommender.neural.GMF: Number of latent factors
numFactors - Variable in class es.upm.etsisi.cf4j.recommender.neural.MLP: Number of factors
numFactorsGMF - Variable in class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Number of GMF latent factors
numFactorsMLP - Variable in class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Number of MLP latent factors
numIters - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Number of iterations
numIters - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Number of iterations
numIters - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Number of iterations
numIters - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF: Number of iterations
numIters - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.NMF: Number of iterations
numIters - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: Number of iterations
numIters - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: Number of iterations
numIters - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Number of iterations

P

p - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: User factors
p - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: User factors
p - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: p parameter
Parallelizer - Class in es.upm.etsisi.cf4j.util.process: This class is used to simplify the parallelization of collaborative filtering algorithms
Parallelizer() - Constructor for class es.upm.etsisi.cf4j.util.process.Parallelizer
ParamsGrid - Class in es.upm.etsisi.cf4j.util.optimization: This class generates the development set for a grid search.
ParamsGrid() - Constructor for class es.upm.etsisi.cf4j.util.optimization.ParamsGrid: Creates a new ParamsGrid
Partible<T> - Interface in es.upm.etsisi.cf4j.util.process: This interface handles the parallel execution of an array of T thorough Parallelizer class.
Perfect - Class in es.upm.etsisi.cf4j.qualityMeasure.prediction: This class calculates the percentage of perfect predictions.
Perfect(Recommender, double) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.prediction.Perfect: Constructor of the class which basically calls the father's one
Perfect(Recommender, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.prediction.Perfect: Constructor from a Map object with the quality measure parameters.
phi - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Phi parameter
PIP - Class in es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric: This class implements the PIP CF similarity metric for the items.
PIP - Class in es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric: Implements the following CF similarity metric: Ahn, H.
PIP() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.PIP
PIP() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.PIP
Plot - Class in es.upm.etsisi.cf4j.util.plot: Abstract class that represents a CF4J plot.
Plot() - Constructor for class es.upm.etsisi.cf4j.util.plot.Plot
PlotSettings - Class in es.upm.etsisi.cf4j.util.plot: This class contains global plot settings.
PMF - Class in es.upm.etsisi.cf4j.recommender.matrixFactorization: Implements Mnih, A., & Salakhutdinov, R.
PMF(DataModel, int, int) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: Model constructor
PMF(DataModel, int, int, double) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: Model constructor
PMF(DataModel, int, int, double, double, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: Model constructor
PMF(DataModel, int, int, double, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: Model constructor
PMF(DataModel, int, int, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: Model constructor
PMF(DataModel, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: Model constructor from a Map containing the model's hyper-parameters values.
PMFRandomSearchCV - Class in es.upm.etsisi.cf4j.examples.gridSearch: In this example we tune the hyper-parameters of PMF recommender using the RandomSearchCV tool.
PMFRandomSearchCV() - Constructor for class es.upm.etsisi.cf4j.examples.gridSearch.PMFRandomSearchCV
Precision - Class in es.upm.etsisi.cf4j.qualityMeasure.recommendation: This class calculates the precision of the recommendations performed by a Recommender.
Precision(Recommender, int, double) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.recommendation.Precision: Constructor of Precision
Precision(Recommender, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.recommendation.Precision: Constructor from a Map object with the quality measure parameters.
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.knn.ItemKNN
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.knn.UserKNN
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BeMF
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.DeepMF
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.DirMF
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.NMF
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.neural.GMF: Returns the prediction of a rating of a certain user for a certain item, through these predictions the metrics of MAE, MSE and RMSE can be obtained.
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.neural.MLP: Returns the prediction of a rating of a certain user for a certain item, through these predictions the metrics of MAE, MSE and RMSE can be obtained.
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.neural.NCCF: Computes the probability that an item will be of interest to the user.
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.neural.NeuMF: Returns the prediction of a rating of a certain user for a certain item, through these predictions the metrics of MAE, MSE and RMSE can be obtained.
predict(int, int) - Method in class es.upm.etsisi.cf4j.recommender.Recommender: Computes a rating prediction
predict(TestUser) - Method in class es.upm.etsisi.cf4j.recommender.Recommender: Computes the rating predictions of the TestItems rated by a TestUser
predictProba(int, int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BeMF: Computes a prediction probability
predictProba(int, int) - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.DirMF: Computes a prediction probability
printData() - Method in class es.upm.etsisi.cf4j.util.plot.HistogramPlot
printData() - Method in class es.upm.etsisi.cf4j.util.plot.Plot: Prints the plot data into the standard output
printData(String) - Method in class es.upm.etsisi.cf4j.util.plot.HistogramPlot
printData(String) - Method in class es.upm.etsisi.cf4j.util.plot.Plot: Prints the plot data into the standard output
printData(String, String) - Method in class es.upm.etsisi.cf4j.util.plot.Plot: Prints the plot data into the standard output
printResults(int) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearch: Prints the results of the random search.
printResults(int) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: Prints the results of the random search.
printResults(int, boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearch: Prints the results of the random search.
printResults(int, boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: Prints the results of the random search.
printResults(int, int, boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearch: Prints the results of the random search.
printResults(int, int, boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: Prints the results of the random search.
printResults(String, int, int, boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearch: Prints the results of the random search.
printResults(String, int, int, boolean) - Method in class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: Prints the results of the random search.

Q

q - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF: Item factors
q - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF: Item factors
q - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: q parameter
QualityMeasure - Class in es.upm.etsisi.cf4j.qualityMeasure: Abstract class used to simplify the evaluation of collaborative filtering based recommendation models.
QualityMeasure(Recommender) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.QualityMeasure: Creates a new quality measure

R

r - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF: Hyper-parameter of the binomial distribution.
R2 - Class in es.upm.etsisi.cf4j.qualityMeasure.prediction: This class calculates the the coefficient of determination, usually denoted as R2, of the predictions performed by a recommender.
R2(Recommender) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.prediction.R2: Constructor of the class which basically calls the father's one
RandomSearch - Class in es.upm.etsisi.cf4j.util.optimization: Utility class to performs a random search over a Recommender instance.
RandomSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], double) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearch: RandomSearch constructor
RandomSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], double, long) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearch: RandomSearch constructor
RandomSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], int) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearch: RandomSearch constructor
RandomSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], Map<String, Object>[], double) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearch: RandomSearch constructor
RandomSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], Map<String, Object>[], double, long) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearch: RandomSearch constructor
RandomSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], Map<String, Object>[], int) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearch: RandomSearch constructor
RandomSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], Map<String, Object>[], int, long) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearch: RandomSearch constructor
RandomSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], Map<String, Object>[], int, long, String) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearch: RandomSearch constructor to be used inside es.upm.etsisi.cf4j.util.optimization package
RandomSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, double) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearch: RandomSearch constructor
RandomSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, double, long) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearch: RandomSearch constructor
RandomSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, int) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearch: RandomSearch constructor
RandomSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, Map<String, Object>, double) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearch: RandomSearch constructor
RandomSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, Map<String, Object>, double, long) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearch: RandomSearch constructor
RandomSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, Map<String, Object>, int) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearch: RandomSearch constructor
RandomSearch(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, Map<String, Object>, int, long) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearch: RandomSearch constructor
RandomSearchCV - Class in es.upm.etsisi.cf4j.util.optimization: Utility class to performs a random search over a Recommender instance.
RandomSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], int, double) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: RandomSearchCV constructor
RandomSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], int, double, long) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: RandomSearchCV constructor
RandomSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], int, int) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: RandomSearchCV constructor
RandomSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], Map<String, Object>[], int, double) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: RandomSearchCV constructor
RandomSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], Map<String, Object>[], int, double, long) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: RandomSearchCV constructor
RandomSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], Map<String, Object>[], int, int) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: RandomSearchCV constructor
RandomSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>[], Map<String, Object>[], int, int, long) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: RandomSearchCV constructor
RandomSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, int, double) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: RandomSearchCV constructor
RandomSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, int, double, long) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: RandomSearchCV constructor
RandomSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, int, int) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: RandomSearchCV constructor
RandomSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, Map<String, Object>, int, double) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: RandomSearchCV constructor
RandomSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, Map<String, Object>, int, double, long) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: RandomSearchCV constructor
RandomSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, Map<String, Object>, int, int) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: RandomSearchCV constructor
RandomSearchCV(DataModel, ParamsGrid, Class<? extends Recommender>, Class<? extends QualityMeasure>, Map<String, Object>, int, int, long) - Constructor for class es.upm.etsisi.cf4j.util.optimization.RandomSearchCV: RandomSearchCV constructor
RandomSplitDataSet - Class in es.upm.etsisi.cf4j.data: This class implements the DataSet interface by random splitting the collaborative filtering ratings allocated in a text file.
RandomSplitDataSet(String) - Constructor for class es.upm.etsisi.cf4j.data.RandomSplitDataSet: Generates a DataSet form a text file.
RandomSplitDataSet(String, double, double) - Constructor for class es.upm.etsisi.cf4j.data.RandomSplitDataSet: Generates a DataSet form a text file.
RandomSplitDataSet(String, double, double, long) - Constructor for class es.upm.etsisi.cf4j.data.RandomSplitDataSet: Generates a DataSet form a text file.
RandomSplitDataSet(String, double, double, String) - Constructor for class es.upm.etsisi.cf4j.data.RandomSplitDataSet: Generates a DataSet form a text file.
RandomSplitDataSet(String, double, double, String, long) - Constructor for class es.upm.etsisi.cf4j.data.RandomSplitDataSet: Generates a DataSet form a text file.
RandomSplitDataSet(String, String) - Constructor for class es.upm.etsisi.cf4j.data.RandomSplitDataSet: Generates a DataSet form a text file.
range(int) - Static method in class es.upm.etsisi.cf4j.util.Maths: Returns an array of int values.
range(int, int) - Static method in class es.upm.etsisi.cf4j.util.Maths: Returns an array of int values.
range(int, int, int) - Static method in class es.upm.etsisi.cf4j.util.Maths: Returns an array of int values.
range(int, int, int, boolean) - Static method in class es.upm.etsisi.cf4j.util.Maths: Returns an array of int values.
rating - Variable in class es.upm.etsisi.cf4j.data.types.DataSetEntry: Rating value
Rating - Class in es.upm.etsisi.cf4j.data.types: The class Rating is an structure of a pair of elements, which are the index and the rating.
Rating(int, double) - Constructor for class es.upm.etsisi.cf4j.data.types.Rating: Creates a new instance
ratings - Variable in class es.upm.etsisi.cf4j.data.ManualDataSet: Raw stored ratings
ratings - Variable in class es.upm.etsisi.cf4j.data.RandomSplitDataSet: Raw stored ratings
ratings - Variable in class es.upm.etsisi.cf4j.data.TrainTestFilesDataSet: Raw stored ratings
ratings - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Plausible ratings (must be sorted in ascending order)
Recall - Class in es.upm.etsisi.cf4j.qualityMeasure.recommendation: This class calculates the recall of the recommendations performed by a Recommender.
Recall(Recommender, int, double) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.recommendation.Recall: Constructor
Recall(Recommender, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.recommendation.Recall: Constructor from a Map object with the quality measure parameters.
recommender - Variable in class es.upm.etsisi.cf4j.qualityMeasure.QualityMeasure: Recommender instance for which the quality measure are going to be computed
Recommender - Class in es.upm.etsisi.cf4j.recommender: Abstract class that represents any recommender.
Recommender(DataModel) - Constructor for class es.upm.etsisi.cf4j.recommender.Recommender: Recommender constructor
RMSE - Class in es.upm.etsisi.cf4j.qualityMeasure.prediction: This class calculates the Root Mean Squared Error (RMSE) between the predictions and the test ratings.
RMSE(Recommender) - Constructor for class es.upm.etsisi.cf4j.qualityMeasure.prediction.RMSE: Constructor of the class which basically calls the father's one
run(Item) - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.ItemSimilarityMetric
run(User) - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.UserSimilarityMetric
run(T) - Method in interface es.upm.etsisi.cf4j.util.process.Partible: Is executed once for each object in the array of objects passed as parameter in the exec method of the Parallelizer class.

S

save(String) - Method in class es.upm.etsisi.cf4j.data.DataModel: Saves the content of the DataModel in a serialized file.
ScatterPlot - Class in es.upm.etsisi.cf4j.util.plot: Implements an ScatterPlot.
ScatterPlot(String, String) - Constructor for class es.upm.etsisi.cf4j.util.plot.ScatterPlot: Creates new ScatterPlot
ScatterPlotExample - Class in es.upm.etsisi.cf4j.examples.plot: In this example we build an ScatterPlot comparing the number of ratings of each test user with his/her averaged prediction error using BiasedMF as recommender.
ScatterPlotExample() - Constructor for class es.upm.etsisi.cf4j.examples.plot.ScatterPlotExample
Search - Class in es.upm.etsisi.cf4j.util: This class contains useful search methods.
Search() - Constructor for class es.upm.etsisi.cf4j.util.Search
setBackgroundColor(Color) - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Sets the plot's background color
setBoolean(String, boolean) - Method in class es.upm.etsisi.cf4j.data.DataBank: Sets or stores a boolean inside the DataBank.
setBooleanArray(String, boolean[]) - Method in class es.upm.etsisi.cf4j.data.DataBank: Sets or stores a boolean array inside the DataBank.
setClearInset(double) - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Sets the inset for a clear border
setColorPalette(Color[]) - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Sets the color paletee
setDatamodel(DataModel) - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.ItemSimilarityMetric: Sets the DataModel for which the similarity are going to be computed
setDatamodel(DataModel) - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.UserSimilarityMetric: Sets the DataModel for which the similarity are going to be computed
setDouble(String, double) - Method in class es.upm.etsisi.cf4j.data.DataBank: Sets or stores a double inside the DataBank.
setDoubleArray(String, double[]) - Method in class es.upm.etsisi.cf4j.data.DataBank: Sets or stores a double array inside the DataBank.
setHeight(int) - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Sets the plot height in pixels
setInt(String, int) - Method in class es.upm.etsisi.cf4j.data.DataBank: Sets or stores an int inside the DataBank.
setIntArray(String, int[]) - Method in class es.upm.etsisi.cf4j.data.DataBank: Sets or stores an int array inside the DataBank.
setLabelsNotVisible(String) - Method in class es.upm.etsisi.cf4j.util.plot.XYPlot: Set the labels not visible for a series
setLabelsVisible(String) - Method in class es.upm.etsisi.cf4j.util.plot.XYPlot: Set the labels visible for a series
setLegendDistance(double) - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Sets the legend distance
setLegendFont(Font) - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Sets the legend font
setLegendInset(double) - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Sets the inset for the legend
setPointsFont(Font) - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Sets the points font
setPrimaryFont(Font) - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Sets the labels font
setRating(double) - Method in class es.upm.etsisi.cf4j.data.types.Rating: Modifies the previously defined rating.
setString(String, String) - Method in class es.upm.etsisi.cf4j.data.DataBank: Sets or stores an String inside the DataBank.
setStringArray(String, String[]) - Method in class es.upm.etsisi.cf4j.data.DataBank: Sets or stores a double array inside the DataBank.
setTicksFont(Font) - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Sets the ticks font
setValue(String, double, double) - Method in class es.upm.etsisi.cf4j.util.plot.LinePlot: Sets a single value of a series
setValue(String, int, double) - Method in class es.upm.etsisi.cf4j.util.plot.LinePlot: Sets a single value of a series
setWidth(int) - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Sets the plot width in pixels
setxAxisInset(double) - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Sets the inset for the x axis
setxAxisLabelDistance(double) - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Sets the label distance in the x axis
setXY(String, String, double, double) - Method in class es.upm.etsisi.cf4j.util.plot.XYPlot: Sets a single point of a series
setyAxisInset(double) - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Sets the inset for the y axis
setyAxisLabelDistance(double) - Static method in class es.upm.etsisi.cf4j.util.plot.PlotSettings: Sets the label distance in the y axis
similarities - Variable in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.ItemSimilarityMetric: Matrix that contains the similarity between each pair of items
similarities - Variable in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.UserSimilarityMetric: Matrix that contains the similarity between each pair of users
similarity(Item, Item) - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.AdjustedCosine
similarity(Item, Item) - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.Correlation
similarity(Item, Item) - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.CorrelationConstrained
similarity(Item, Item) - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.Cosine
similarity(Item, Item) - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.ItemSimilarityMetric: This method must returns the similarity between two items.
similarity(Item, Item) - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.Jaccard
similarity(Item, Item) - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.JMSD
similarity(Item, Item) - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.MSD
similarity(Item, Item) - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.PIP
similarity(Item, Item) - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.Singularities
similarity(Item, Item) - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.SpearmanRank
similarity(User, User) - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.AdjustedCosine
similarity(User, User) - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.CJMSD
similarity(User, User) - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.Correlation
similarity(User, User) - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.CorrelationConstrained
similarity(User, User) - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.Cosine
similarity(User, User) - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.Jaccard
similarity(User, User) - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.JMSD
similarity(User, User) - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.MSD
similarity(User, User) - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.PIP
similarity(User, User) - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.Singularities
similarity(User, User) - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.SpearmanRank
similarity(User, User) - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.UserSimilarityMetric: This method must returns the similarity between two users.
Singularities - Class in es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric: This class implements the singularities CF similarity metric.
Singularities - Class in es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric: Implements the following CF similarity metric: Bobadilla, J., Ortega, F., & Hernando, A
Singularities(double[], double[]) - Constructor for class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.Singularities: Constructor of the similarity metric
Singularities(double[], double[]) - Constructor for class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.Singularities: Constructor of the similarity metric
SortedRatingList - Class in es.upm.etsisi.cf4j.data.types: SortedRatingList is a specific type of sorted ArrayList that uses the Rating class internally.
SortedRatingList() - Constructor for class es.upm.etsisi.cf4j.data.types.SortedRatingList
SpearmanRank - Class in es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric: Implements traditional Spearman Rank as CF similarity metric for the items.
SpearmanRank - Class in es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric: Implements traditional Spearman Rank as CF similarity metric.
SpearmanRank() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.SpearmanRank
SpearmanRank() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.SpearmanRank
SVDPlusPlus - Class in es.upm.etsisi.cf4j.recommender.matrixFactorization: Implements Koren, Y. (2008, August).
SVDPlusPlus(DataModel, int, int) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: Model constructor
SVDPlusPlus(DataModel, int, int, double, double) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: Model constructor
SVDPlusPlus(DataModel, int, int, double, double, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: Model constructor
SVDPlusPlus(DataModel, int, int, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: Model constructor
SVDPlusPlus(DataModel, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: Model constructor from a Map containing the model's hyper-parameters values.

T

tauRte - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
tauShp - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
TestItem - Class in es.upm.etsisi.cf4j.data: A TestItem extends an Item given it the following properties: Index in the DataModel array which stores test items.
TestItem(String, int, int) - Constructor for class es.upm.etsisi.cf4j.data.TestItem: Creates a new instance of a test item.
testItemIndex - Variable in class es.upm.etsisi.cf4j.data.TestItem: Index in the DataModel array which stores test items
testItemsRatings - Variable in class es.upm.etsisi.cf4j.data.TestUser: TestItems rated by the user
testRatings - Variable in class es.upm.etsisi.cf4j.data.ManualDataSet: Raw stored test ratings
testRatings - Variable in class es.upm.etsisi.cf4j.data.RandomSplitDataSet: Raw stored test ratings
testRatings - Variable in class es.upm.etsisi.cf4j.data.TrainTestFilesDataSet: Raw stored test ratings
TestUser - Class in es.upm.etsisi.cf4j.data: A TestUser extends an User given him or her the following properties: Index in the DataModel array which stores test users.
TestUser(String, int, int) - Constructor for class es.upm.etsisi.cf4j.data.TestUser: Creates a new instance of a test user.
testUserIndex - Variable in class es.upm.etsisi.cf4j.data.TestUser: Index in the DataModel array which stores test users
testUsersRatings - Variable in class es.upm.etsisi.cf4j.data.TestItem: Array of test users that have rated this test item
threshold - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Threshold to binarize rating matrix.
toString() - Method in class es.upm.etsisi.cf4j.data.DataModel
toString() - Method in class es.upm.etsisi.cf4j.data.types.DataSetEntry
toString() - Method in class es.upm.etsisi.cf4j.data.types.Rating
toString() - Method in class es.upm.etsisi.cf4j.recommender.knn.ItemKNN
toString() - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.CorrelationConstrained
toString() - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.ItemSimilarityMetric
toString() - Method in class es.upm.etsisi.cf4j.recommender.knn.itemSimilarityMetric.Singularities
toString() - Method in class es.upm.etsisi.cf4j.recommender.knn.UserKNN
toString() - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.CorrelationConstrained
toString() - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.Singularities
toString() - Method in class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.UserSimilarityMetric
toString() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BeMF
toString() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BiasedMF
toString() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.BNMF
toString() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF
toString() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.DeepMF
toString() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.DirMF
toString() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.HPF
toString() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.NMF
toString() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.PMF
toString() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus
toString() - Method in class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP
toString() - Method in class es.upm.etsisi.cf4j.recommender.neural.GMF
toString() - Method in class es.upm.etsisi.cf4j.recommender.neural.MLP
toString() - Method in class es.upm.etsisi.cf4j.recommender.neural.NCCF
toString() - Method in class es.upm.etsisi.cf4j.recommender.neural.NeuMF
toString() - Method in class es.upm.etsisi.cf4j.util.plot.HistogramPlot
toString() - Method in class es.upm.etsisi.cf4j.util.plot.Plot
toString(String) - Method in class es.upm.etsisi.cf4j.util.plot.HistogramPlot
toString(String) - Method in class es.upm.etsisi.cf4j.util.plot.Plot: Stringify the plot data
toString(String, String) - Method in class es.upm.etsisi.cf4j.util.plot.Plot: Stringify the plot data
TrainTestFilesDataSet - Class in es.upm.etsisi.cf4j.data: This class implements the DataSet interface by loading training and test ratings from separated text files.
TrainTestFilesDataSet(String, String) - Constructor for class es.upm.etsisi.cf4j.data.TrainTestFilesDataSet: Generates a DataSet form training and test ratings files.
TrainTestFilesDataSet(String, String, String) - Constructor for class es.upm.etsisi.cf4j.data.TrainTestFilesDataSet: Generates a DataSet form training and test ratings files.

U

U - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Users' latent factors
URP - Class in es.upm.etsisi.cf4j.recommender.matrixFactorization: Implements Marlin, B.
URP(DataModel, int, double[], int) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Model constructor
URP(DataModel, int, double[], int, double) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Model constructor
URP(DataModel, int, double[], int, double, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Model constructor
URP(DataModel, int, double[], int, long) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Model constructor
URP(DataModel, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.recommender.matrixFactorization.URP: Model constructor from a Map containing the model's hyper-parameters values.
User - Class in es.upm.etsisi.cf4j.data: Defines a composition of an User.
User(String, int) - Constructor for class es.upm.etsisi.cf4j.data.User: Creates a new instance of an user.
userId - Variable in class es.upm.etsisi.cf4j.data.types.DataSetEntry: Identifier of the user who rated this item
userIndex - Variable in class es.upm.etsisi.cf4j.data.User: User index in the DataModel
UserKNN - Class in es.upm.etsisi.cf4j.recommender.knn: Implements user-to-user KNN based collaborative filtering
UserKNN(DataModel, int, UserSimilarityMetric, UserKNN.AggregationApproach) - Constructor for class es.upm.etsisi.cf4j.recommender.knn.UserKNN: Recommender constructor
UserKNN(DataModel, Map<String, Object>) - Constructor for class es.upm.etsisi.cf4j.recommender.knn.UserKNN: Recommender constructor from a Map containing the recommender's hyper-parameters values.
UserKNN.AggregationApproach - Enum in es.upm.etsisi.cf4j.recommender.knn: Available aggregation approaches to merge k-nearest neighbors ratings
UserKnnComparison - Class in es.upm.etsisi.cf4j.examples.recommender: In this example we compare the MAE, Coverage, Precision and Recall quality measures scores for different similarity metrics applied to user-to-user knn based collaborative filtering.
UserKnnComparison() - Constructor for class es.upm.etsisi.cf4j.examples.recommender.UserKnnComparison
UserKNNGridSearch - Class in es.upm.etsisi.cf4j.examples.gridSearch: In this example we tune the parameters of UserKNN recommender using the GridSearch tool.
UserKNNGridSearch() - Constructor for class es.upm.etsisi.cf4j.examples.gridSearch.UserKNNGridSearch
UserSimilarityMetric - Class in es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric: This class process the similarity measure between two users.
UserSimilarityMetric() - Constructor for class es.upm.etsisi.cf4j.recommender.knn.userSimilarityMetric.UserSimilarityMetric
usersRatings - Variable in class es.upm.etsisi.cf4j.data.Item: Users that have rated the item

V

V - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.CLiMF: Items's latent factors
valueOf(String) - Static method in enum es.upm.etsisi.cf4j.recommender.knn.ItemKNN.AggregationApproach: Returns the enum constant of this type with the specified name.
valueOf(String) - Static method in enum es.upm.etsisi.cf4j.recommender.knn.UserKNN.AggregationApproach: Returns the enum constant of this type with the specified name.
values() - Static method in enum es.upm.etsisi.cf4j.recommender.knn.ItemKNN.AggregationApproach: Returns an array containing the constants of this enum type, in the order they are declared.
values() - Static method in enum es.upm.etsisi.cf4j.recommender.knn.UserKNN.AggregationApproach: Returns an array containing the constants of this enum type, in the order they are declared.

W

w - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.NMF: User factors
WEIGHTED_MEAN - es.upm.etsisi.cf4j.recommender.knn.ItemKNN.AggregationApproach
WEIGHTED_MEAN - es.upm.etsisi.cf4j.recommender.knn.UserKNN.AggregationApproach

X

XYPlot - Class in es.upm.etsisi.cf4j.util.plot: Implements an XYPlot.
XYPlot(String[], String, String) - Constructor for class es.upm.etsisi.cf4j.util.plot.XYPlot: Creates a new XYPlot
XYPlot(String[], String, String, boolean) - Constructor for class es.upm.etsisi.cf4j.util.plot.XYPlot: Creates a new XYPlot
XYPlotExample - Class in es.upm.etsisi.cf4j.examples.plot: In this example we compare the Precision score (y axis) and the Recall score (x axis) for PMF and NMF recommenders using an XYPlot.
XYPlotExample() - Constructor for class es.upm.etsisi.cf4j.examples.plot.XYPlotExample

Y

y - Variable in class es.upm.etsisi.cf4j.recommender.matrixFactorization.SVDPlusPlus: y parameter

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