Overview | Package | Class | Use | Tree | Deprecated | Index | Help
PREV LETTER NEXT LETTER | FRAMES NO FRAMES

A B C D E F G H I K L M N O P Q R S T U V W X

## R

Random - Class in prea.recommender.baseline
  The class implementing a baseline, predicting uniformly randomly from the score range.
Random(int, int, double, double) - Constructor for class prea.recommender.baseline.Random
  Construct a constant model with the given data.
RankBased - Class in prea.recommender.etc
  This is a class implementing rank-based collaborative filtering.
RankBased(int, int, double, double, double, int) - Constructor for class prea.recommender.etc.RankBased
  Construct a rank-based model with the given data.
rankBasedPerUser(int, int, double, int, int[], double[], SparseVector[], SparseMatrix[]) - Method in class prea.recommender.etc.RankBased
  Predict ratings for a given user and a given test item, by rank-based CF algorithm.
rateMatrix - Variable in class prea.data.splitter.DataSplitManager
  Rating matrix for each user (row) and item (column)
rateMatrix - Static variable in class prea.main.Prea
  Rating matrix for each user (row) and item (column)
rateMatrix - Static variable in class prea.main.Splitter
  Rating matrix for train dataset.
rateMatrix - Variable in class prea.recommender.baseline.BaselineRecommender
  Rating matrix for each user (row) and item (column)
rateMatrix - Variable in class prea.recommender.CustomRecommender
  Rating matrix for each user (row) and item (column)
rateMatrix - Variable in class prea.recommender.etc.FastNPCA
  Rating matrix for each user (row) and item (column)
rateMatrix - Variable in class prea.recommender.etc.NonlinearPMF
  Rating matrix for each user (row) and item (column)
rateMatrix - Variable in class prea.recommender.etc.RankBased
  Rating matrix for each user (row) and item (column)
rateMatrix - Variable in class prea.recommender.etc.SlopeOne
  Rating matrix for each user (row) and item (column)
rateMatrix - Variable in class prea.recommender.memory.MemoryBasedRecommender
  Rating matrix for each user (row) and item (column)
rbfKernCompute(DenseMatrix, double, double) - Method in class prea.recommender.etc.NonlinearPMF
  Compute RBF(radial basis function) kernel parameters for given distances.
rbfKernGradXpoint(DenseVector, DenseMatrix, double, double) - Method in class prea.recommender.etc.NonlinearPMF
  Compute the gradient of RBF kernel with respect to input locations.
readArff(String) - Static method in class prea.main.Prea
  Read the data file in ARFF format, and store it in rating matrix.
readArff(String) - Static method in class prea.main.Splitter
  Read the data file in ARFF format, and store it in rating matrix.
readItemSimData(int[]) - Method in class prea.recommender.memory.ItemBased
  Read the pre-calculated item similarity data file.
readSplitData(String) - Method in class prea.data.splitter.PredefinedSplit
  Split the rating matrix into train and test set, by given split data file.
recommendCount - Variable in class prea.util.EvaluationMetrics
  The number of items to recommend, in rank-based metrics
Recommender - Interface in prea.recommender
  Interface of general recommendation system.
recoverTestItems() - Method in class prea.data.splitter.DataSplitManager
  Items in testMatrix are moved back to original rateMatrix.
RegularizedSVD - Class in prea.recommender.matrix
  This is a class implementing Regularized SVD (Singular Value Decomposition).
RegularizedSVD(int, int, double, double, int, double, double, double, int, boolean) - Constructor for class prea.recommender.matrix.RegularizedSVD
  Construct a matrix-factorization model with the given data.
regularizer - Variable in class prea.recommender.matrix.MatrixFactorizationRecommender
  Regularization factor parameter.
remove(Key) - Method in class prea.data.structure.DataMap
  Remove a data element with the given key.
remove(int) - Method in class prea.data.structure.DenseVector
  Delete a value stored at the given index.
remove(int) - Method in class prea.data.structure.SparseVector
  Delete a value stored at the given index.
restoreValidationSet() - Method in class prea.recommender.etc.FastNPCA
  Items in validationMatrix are moved to original rateMatrix.
restoreValidationSet(SparseMatrix) - Method in class prea.recommender.matrix.NMF
  Items in validationMatrix are moved to original rateMatrix.
rows - Variable in class prea.data.structure.SparseMatrix
  The array of row references.
run() - Static method in class prea.main.Prea
  Run an/all algorithm with given data, based on the setting from command arguments.
runAll() - Static method in class prea.main.Prea
  Run all algorithms with given data.
runAllAlgorithms - Static variable in class prea.main.Prea
  Indicating whether to run all algorithms.
runIndividual(String, String[]) - Static method in class prea.main.Prea
  Run one algorithm with customized parameters with given data.

Overview | Package | Class | Use | Tree | Deprecated | Index | Help
PREV LETTER NEXT LETTER | FRAMES NO FRAMES

A B C D E F G H I K L M N O P Q R S T U V W X