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parseCommandLine(String[])
- Static method in class prea.main.
Prea
Parse the command from user.
partInnerProduct(DenseVector, int[])
- Method in class prea.data.structure.
DenseVector
Inner-product for indices only in the given indices.
partInnerProduct(SparseVector, int[])
- Method in class prea.data.structure.
SparseVector
Inner-product for indices only in the given indices.
partInverse(int[])
- Method in class prea.data.structure.
DenseMatrix
Inverse of matrix only with indices in indexList.
partInverse(int[])
- Method in class prea.data.structure.
SparseMatrix
Inverse of matrix only with indices in indexList.
partition(int[], int, int, boolean)
- Static method in class prea.util.
Sort
Partition the given array into two section: smaller and larger than threshold.
partition(double[], int[], int, int, boolean)
- Static method in class prea.util.
Sort
Partition the given array into two section: smaller and larger than threshold.
partition(int[], int[], int, int, boolean)
- Static method in class prea.util.
Sort
Partition the given array into two section: smaller and larger than threshold.
partition(int[], double[], int, int, boolean)
- Static method in class prea.util.
Sort
Partition the given array into two section: smaller and larger than threshold.
partMinus(DenseMatrix, int[])
- Method in class prea.data.structure.
DenseMatrix
Matrix subtraction (A = A - B) only with indices in indexList.
partMinus(DenseVector, int[])
- Method in class prea.data.structure.
DenseVector
Vector subtraction (a - b) for indices only in the given indices.
partMinus(SparseMatrix, int[])
- Method in class prea.data.structure.
SparseMatrix
Matrix subtraction (A = A - B) only with indices in indexList.
partMinus(SparseVector, int[])
- Method in class prea.data.structure.
SparseVector
Vector subtraction (a - b) for indices only in the given indices.
partOuterProduct(DenseVector, int[])
- Method in class prea.data.structure.
DenseVector
Outer-product for indices only in the given indices.
partOuterProduct(SparseVector, int[])
- Method in class prea.data.structure.
SparseVector
Outer-product for indices only in the given indices.
partPlus(DenseMatrix, int[])
- Method in class prea.data.structure.
DenseMatrix
Matrix summation (A = A + B) only with indices in indexList.
partPlus(DenseVector, int[])
- Method in class prea.data.structure.
DenseVector
Vector sum (a + b) for indices only in the given indices.
partPlus(SparseMatrix, int[])
- Method in class prea.data.structure.
SparseMatrix
Matrix summation (A = A + B) only with indices in indexList.
partPlus(SparseVector, int[])
- Method in class prea.data.structure.
SparseVector
Vector sum (a + b) for indices only in the given indices.
partScale(double, int[])
- Method in class prea.data.structure.
DenseMatrix
Scalar Multiplication only with indices in indexList.
partScale(double, int[])
- Method in class prea.data.structure.
SparseMatrix
Scalar Multiplication only with indices in indexList.
partTimes(DenseVector, int[])
- Method in class prea.data.structure.
DenseMatrix
Matrix-vector product (b = Ax) only with indices in indexList.
partTimes(SparseVector, int[])
- Method in class prea.data.structure.
SparseMatrix
Matrix-vector product (b = Ax) only with indices in indexList.
PEARSON_CORR
- Static variable in class prea.main.
Splitter
Similarity measure code for Pearson Correlation.
PEARSON_CORR
- Static variable in class prea.recommender.memory.
MemoryBasedRecommender
Similarity Measure Code for Pearson Correlation
plus(DenseMatrix)
- Method in class prea.data.structure.
DenseMatrix
Matrix-matrix sum (C = A + B)
plus(DenseVector)
- Method in class prea.data.structure.
DenseVector
Vector sum (a + b)
plus(SparseMatrix)
- Method in class prea.data.structure.
SparseMatrix
Matrix-matrix sum (C = A + B)
plus(SparseVector)
- Method in class prea.data.structure.
SparseVector
Vector sum (a + b)
PMF
- Class in
prea.recommender.matrix
This is a class implementing Probabilistic Matrix Factorization.
PMF(int, int, double, double, int, double, double, double, int, boolean)
- Constructor for class prea.recommender.matrix.
PMF
Construct a matrix-factorization model with the given data.
power(double)
- Method in class prea.data.structure.
DenseVector
Scalar power operator.
power(double)
- Method in class prea.data.structure.
SparseVector
Scalar power operator.
prbMatricesIndTrain
- Variable in class prea.recommender.etc.
RankBased
Parsed index for each user, 2d array with m testing users by the number of rated items.
prbMatricesVal
- Variable in class prea.recommender.etc.
RankBased
Parsed prb for each user, 3d array with l rating levels by m testing users by the number of rated items.
Prea
- Class in
prea.main
The main class of this toolkit.
Prea()
- Constructor for class prea.main.
Prea
prea.data.splitter
- package prea.data.splitter
prea.data.structure
- package prea.data.structure
prea.main
- package prea.main
prea.recommender
- package prea.recommender
prea.recommender.baseline
- package prea.recommender.baseline
prea.recommender.etc
- package prea.recommender.etc
prea.recommender.matrix
- package prea.recommender.matrix
prea.recommender.memory
- package prea.recommender.memory
prea.util
- package prea.util
PREDEFINED_SPLIT
- Static variable in class prea.data.splitter.
DataSplitManager
Use predefined split file.
PredefinedSplit
- Class in
prea.data.splitter
When a predefined split file is available, this class helps to split train/test set as defined in the file.
PredefinedSplit(SparseMatrix, String, int, int)
- Constructor for class prea.data.splitter.
PredefinedSplit
Construct an instance for splitter with predefined split file.
predict(int, int)
- Method in class prea.recommender.baseline.
Average
Predict a rating for the given user and item.
predict(int, int)
- Method in class prea.recommender.baseline.
BaselineRecommender
Predict a rating for the given user and item.
predict(int, int)
- Method in class prea.recommender.baseline.
Constant
Predict a rating for the given user and item.
predict(int, int)
- Method in class prea.recommender.baseline.
ItemAverage
Predict a rating for the given user and item.
predict(int, int)
- Method in class prea.recommender.baseline.
Random
Predict a rating for the given user and item.
predict(int, int)
- Method in class prea.recommender.baseline.
UserAverage
Predict a rating for the given user and item.
predict(int, int)
- Method in class prea.recommender.etc.
RankBased
Compute the rating for a given user and a test item, which minimizes the given loss.
predict(int, int[], int, SparseMatrix)
- Method in class prea.recommender.memory.
ItemBased
Predict ratings for a given user regarding given set of items, by user-based CF algorithm.
predict(int, int[], int, double[])
- Method in class prea.recommender.memory.
UserBased
Predict ratings for a given user regarding given set of items, by user-based CF algorithm.
predicted
- Variable in class prea.util.
EvaluationMetrics
Predicted ratings by CF algorithms for test items.
predictedArray
- Variable in class prea.recommender.etc.
RankBased
The probability array of each rating for testing items and users.
preferProbability(double, double)
- Static method in class prea.util.
Distance
Return the probability of the item i is preferred to the item j.
preservedRateMatrix
- Variable in class prea.recommender.
UnitTest
preservedTestMatrix
- Variable in class prea.recommender.
UnitTest
printArray(double[])
- Static method in class prea.util.
Printer
Print each element in a double array.
printArray(int[])
- Static method in class prea.util.
Printer
Print each element in an integer array
printArray(double[][])
- Static method in class prea.util.
Printer
Print each element in a 2-D double matrix.
printArray(double[][][])
- Static method in class prea.util.
Printer
Print each element in a 3-D double matrix.
Printer
- Class in
prea.util
This is a class containing printing functions in human-readable format from various kinds of data.
Printer()
- Constructor for class prea.util.
Printer
printMultiLine()
- Method in class prea.util.
EvaluationMetrics
printOneLine()
- Method in class prea.util.
EvaluationMetrics
printTime(long)
- Static method in class prea.util.
Printer
Convert time in milliseconds to human-readable format.
printTitle()
- Static method in class prea.util.
EvaluationMetrics
put(Key, Val)
- Method in class prea.data.structure.
DataMap
Set a data value with the given key.
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