class NMFactorization extends Reducer
The NMFactorization class factors a matrix 'x' into two non negative matrices
'w' and 'h' such that 'x = wh' approximately.
- See also
en.wikipedia.org/wiki/Non-negative_matrix_factorization
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- new NMFactorization(x: MatriD, loops: Int = 10, r: Int = 0)
- x
the matrix to be factored
- loops
the number of iterations before checking the termination condition
- r
factor the m-by-n matrix 'x' in to two factors: an m-by-r and r-by-n matrix
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- def factorReduce(): (MatrixD, MatrixD)
Factor and reduce the original matrix 'x' into left 'w' and right 'h' matrices by iteratively calling the 'update' method until the difference between 'x' and its reduced approximation 'xr = w * h' is sufficiently small.
Factor and reduce the original matrix 'x' into left 'w' and right 'h' matrices by iteratively calling the 'update' method until the difference between 'x' and its reduced approximation 'xr = w * h' is sufficiently small.
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- NMFactorization → Reducer
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- var r: Int
- def recover(): MatriD
Approximately recover the original matrix.
Approximately recover the original matrix. The new matrix will have the same dimensionality, but will have some lose of information.
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- NMFactorization → Reducer
- def reduce(): MatriD
Reduce the original data matrix by producing a lower dimensionality matrix that maintains most of the descriptive power of the original matrix.
Reduce the original data matrix by producing a lower dimensionality matrix that maintains most of the descriptive power of the original matrix.
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