- class composes.transformation.dim_reduction.svd.Svd(reduced_dimension)¶
Performs truncated Singular Value Decomposition to a reduced dimension \(k\).
Given an input matrix \(X\), it computes the decomposition:
\(X = U \Sigma V^{T}\)
It returns \(U \Sigma\) truncated to dimension \(min(k,rank(X))\)
- class composes.transformation.dim_reduction.nmf.Nmf(reduced_dimension)¶
Performs Non-negative Matrix Factorization to reduced dimension \(k\).
Given an input non-negative matrix \(X\), it computes the decomposition:
\(X \approx WH\) where W and H are non-negative matrices which minimize \(||X-WH||_{2}\)
It returns the matrix W.