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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.
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