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  [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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