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## S

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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