Alternating least squares is often used to resolve components contributing to data with a bilinear structure; the basic technique may be extended to alternating constrained least squares. Commonly applied constraints include unimodality, non-negativity, and normalization of components. Several data matrices may be decomposed simultaneously by assuming that one of the two matrices in the bilinear decomposition is shared between datasets.


Info: This package contains files in non-standard labels.

conda install

  • noarch  v0.0.6
To install this package with conda run one of the following:
conda install -c conda-forge r-als
conda install -c conda-forge/label/gcc7 r-als
conda install -c conda-forge/label/cf201901 r-als


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