RECA: Relevant Component Analysis for Supervised Distance Metric Learning

Relevant Component Analysis (RCA) tries to find a linear transformation of the feature space such that the effect of irrelevant variability is reduced in the transformed space.

Version: 1.7
Suggests: MASS
Published: 2019-05-17
DOI: 10.32614/CRAN.package.RECA
Author: Nan Xiao ORCID iD [aut, cre]
Maintainer: Nan Xiao <me at nanx.me>
BugReports: https://github.com/nanxstats/RECA/issues
License: GPL-3 | file LICENSE
URL: https://nanx.me/RECA/, https://github.com/nanxstats/RECA
NeedsCompilation: no
Materials: README
CRAN checks: RECA results

Documentation:

Reference manual: RECA.pdf

Downloads:

Package source: RECA_1.7.tar.gz
Windows binaries: r-devel: RECA_1.7.zip, r-release: RECA_1.7.zip, r-oldrel: RECA_1.7.zip
macOS binaries: r-release (arm64): RECA_1.7.tgz, r-oldrel (arm64): RECA_1.7.tgz, r-release (x86_64): RECA_1.7.tgz, r-oldrel (x86_64): RECA_1.7.tgz
Old sources: RECA archive

Linking:

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