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.
copied from cf-post-staging / r-als| Label | Latest Version |
|---|---|
| main | 0.0.7 |
| gcc7 | 0.0.6 |
| cf201901 | 0.0.6 |
| cf202003 | 0.0.6 |
