CRAN/E | CMF

CMF

Collective Matrix Factorization

Installation

About

Collective matrix factorization (CMF) finds joint low-rank representations for a collection of matrices with shared row or column entities. This code learns a variational Bayesian approximation for CMF, supporting multiple likelihood potentials and missing data, while identifying both factors shared by multiple matrices and factors private for each matrix. For further details on the method see Klami et al. (2014) . The package can also be used to learn Bayesian canonical correlation analysis (CCA) and group factor analysis (GFA) models, both of which are special cases of CMF. This is likely to be useful for people looking for CCA and GFA solutions supporting missing data and non-Gaussian likelihoods. See Klami et al. (2013) and Virtanen et al. (2012) for details on Bayesian CCA and GFA, respectively.

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Version 1.0.3
Published 2022-08-09 619 days ago
Needs compilation? yes
License GPL-2
License GPL-3
CRAN checks CMF results

Downloads

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Maintainer

Maintainer

Felix Held

felix.held@gmail.com

Authors

Arto Klami

aut

Lauri Väre

aut

Felix Held

ctb / cre

Material

README
Reference manual
Package source

In Views

MissingData

macOS

r-release

arm64

r-oldrel

arm64

r-release

x86_64

r-oldrel

x86_64

Windows

r-devel

x86_64

r-release

x86_64

r-oldrel

x86_64

Old Sources

CMF archive

Imports

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LinkingTo

cpp11