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scale(double)
- Method in class prea.data.structure.
DenseMatrix
Scalar multiplication (aX).
scale(double)
- Method in class prea.data.structure.
DenseVector
Scalar multiplication operator.
scale(double)
- Method in class prea.data.structure.
SparseMatrix
Scalar subtraction (aX).
scale(double)
- Method in class prea.data.structure.
SparseVector
Scalar multiplication operator.
selfAdd(double)
- Method in class prea.data.structure.
DenseMatrix
Scalar addition on the matrix itself.
selfAdd(double)
- Method in class prea.data.structure.
SparseMatrix
Scalar addition on the matrix itself.
selfScale(double)
- Method in class prea.data.structure.
DenseMatrix
Scalar multiplication (aX) on the matrix itself.
selfScale(double)
- Method in class prea.data.structure.
SparseMatrix
Scalar subtraction (aX) on the matrix itself.
selfTimes(SparseMatrix)
- Method in class prea.data.structure.
SparseMatrix
Matrix-matrix product (A = AB), without using extra memory.
setLength(int)
- Method in class prea.data.structure.
DenseVector
Set a new capacity of the vector.
setLength(int)
- Method in class prea.data.structure.
SparseVector
Set a new capacity of the vector.
setSize(int, int)
- Method in class prea.data.structure.
SparseMatrix
Set a new size of the matrix.
setValue(int, int, double)
- Method in class prea.data.structure.
DenseMatrix
Set a new value at the given index.
setValue(int, double)
- Method in class prea.data.structure.
DenseVector
Set a new value at the given index.
setValue(int, int, double)
- Method in class prea.data.structure.
SparseMatrix
Set a new value at the given index.
setValue(int, double)
- Method in class prea.data.structure.
SparseVector
Set a new value at the given index.
showProgress
- Variable in class prea.recommender.etc.
FastNPCA
Indicator whether to show progress of iteration.
showProgress
- Variable in class prea.recommender.etc.
NonlinearPMF
Indicator whether to show progress of iteration.
showProgress
- Variable in class prea.recommender.matrix.
MatrixFactorizationRecommender
Indicator whether to show progress of iteration.
similarity(boolean, SparseVector, SparseVector, double, double, int)
- Static method in class prea.main.
Splitter
Calculate similarity between two given vectors.
similarity(boolean, SparseVector, SparseVector, double, double, int)
- Method in class prea.recommender.memory.
MemoryBasedRecommender
Calculate similarity between two given vectors.
similarityMethod
- Variable in class prea.recommender.memory.
MemoryBasedRecommender
The method code for similarity measure.
SIMPLE_SPLIT
- Static variable in class prea.data.splitter.
DataSplitManager
Randomly split train/test set.
SIMPLE_WEIGHTED_AVG
- Static variable in class prea.recommender.memory.
MemoryBasedRecommender
Estimation Method Code for Simple Weighted Average
SimpleSplit
- Class in
prea.data.splitter
This class helps to split data matrix into train set and test set, based on the test set ratio defined by the user.
SimpleSplit(SparseMatrix, double, int, int)
- Constructor for class prea.data.splitter.
SimpleSplit
Construct an instance for simple splitter.
SlopeOne
- Class in
prea.recommender.etc
This is a class implementing Slope-One algorithm.
SlopeOne(int, int, double, double)
- Constructor for class prea.recommender.etc.
SlopeOne
Construct a Fast NPCA model with the given data.
Sort
- Class in
prea.util
This is a class implementing sort functions in various data type.
Sort()
- Constructor for class prea.util.
Sort
SparseMatrix
- Class in
prea.data.structure
This class implements sparse matrix, containing empty values for most space.
SparseMatrix(int, int)
- Constructor for class prea.data.structure.
SparseMatrix
Construct an empty sparse matrix, with a given size.
SparseMatrix(SparseMatrix)
- Constructor for class prea.data.structure.
SparseMatrix
Construct an empty sparse matrix, with data copied from another sparse matrix.
SparseVector
- Class in
prea.data.structure
This class implements sparse vector, containing empty values for most space.
SparseVector()
- Constructor for class prea.data.structure.
SparseVector
Construct an empty sparse vector, with capacity 0.
SparseVector(int)
- Constructor for class prea.data.structure.
SparseVector
Construct a new sparse vector with size n.
spearman
- Variable in class prea.util.
EvaluationMetrics
Rank-based Spear
split(double)
- Method in class prea.data.splitter.
SimpleSplit
Items which will be used for test purpose are moved from rateMatrix to testMatrix.
splitFileName
- Static variable in class prea.main.
Prea
The name of predefined split data file.
Splitter
- Class in
prea.main
This class helps to save train/test split and similarity prefetch files.
Splitter()
- Constructor for class prea.main.
Splitter
stdev()
- Method in class prea.data.structure.
DenseMatrix
Standard Deviation of every element.
stdev()
- Method in class prea.data.structure.
DenseVector
Standard Deviation of every element.
stdev()
- Method in class prea.data.structure.
SparseMatrix
Standard Deviation of every element.
stdev()
- Method in class prea.data.structure.
SparseVector
Standard Deviation of every element.
sub(double)
- Method in class prea.data.structure.
DenseVector
Scalar subtraction operator.
sub(double)
- Method in class prea.data.structure.
SparseVector
Scalar subtraction operator.
sum()
- Method in class prea.data.structure.
DenseMatrix
Sum of every element.
sum()
- Method in class prea.data.structure.
DenseVector
Sum of every element in the vector.
sum()
- Method in class prea.data.structure.
SparseVector
Sum of every element in the vector.
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