- get(int, int) - Method in class librec.data.DenseMatrix
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Get the value at entry [row, column]
- get(int) - Method in class librec.data.DenseVector
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Get a value at entry [index]
- get() - Method in interface librec.data.MatrixEntry
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Returns the value at the current index
- get(int, int) - Method in class librec.data.SparseMatrix
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Retrieve value at entry [row, column]
- get(int) - Method in class librec.data.SparseVector
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Retrieve a value at entry [idx]
- get(int, int) - Method in class librec.data.SymmMatrix
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Get a value at entry (row, col)
- get() - Method in interface librec.data.VectorEntry
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Returns the value at the current index
- getColumnIndices() - Method in class librec.data.SparseMatrix
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- getCount() - Method in class librec.data.SparseVector
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Number of entries in the sparse structure
- getData() - Method in class librec.data.DenseVector
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- getData() - Method in class librec.data.SparseMatrix
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- getData() - Method in class librec.data.SparseVector
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Returns the internal data
- getDataPath() - Method in class librec.data.DataDAO
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- getDataView(String) - Method in class librec.data.DataSplitter
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- getEvalInfo(Map<Recommender.Measure, Double>) - Static method in class librec.intf.Recommender
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- getGiven(int) - Method in class librec.data.DataSplitter
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Split ratings into two parts: the training set consisting of user-item
ratings where numGiven
ratings are preserved for each user, and
the rest are used as the testing data
- getGiven(double) - Method in class librec.data.DataSplitter
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Split ratings into two parts: the training set consisting of user-item
ratings where numGiven
ratings are preserved for each user, and
the rest are used as the testing data
- getIndex() - Method in class librec.data.SparseVector
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Returns the indices
- getItemId(String) - Method in class librec.data.DataDAO
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- getItemId(int) - Method in class librec.data.DataDAO
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- getItemIds() - Method in class librec.data.DataDAO
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- getKthFold(int) - Method in class librec.data.DataSplitter
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Return the k-th fold as test set (testMatrix), making all the others as
train set in rateMatrix.
- getRateMatrix() - Method in class librec.data.DataDAO
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- getRatio(double) - Method in class librec.data.DataSplitter
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Split ratings into two parts: (1-ratio) training, (ratio) testing data
- getRowPointers() - Method in class librec.data.SparseMatrix
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- getSample(int, int) - Method in class librec.data.DataSplitter
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generate a random sample of rate matrix with specified number of users
and items
- getScales() - Method in class librec.data.DataDAO
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- getUserId(String) - Method in class librec.data.DataDAO
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- getUserId(int) - Method in class librec.data.DataDAO
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- getUserIds() - Method in class librec.data.DataDAO
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- GlobalAverage - Class in librec.baseline
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Baseline: predict by average rating of all users
- GlobalAverage(SparseMatrix, SparseMatrix, int) - Constructor for class librec.baseline.GlobalAverage
-