Cross-validated linear discriminant calculations determine the optimum number of features. Test and training scores from successive cross-validation steps determine, via a principal components calculation, a low-dimensional global space onto which test scores are projected, in order to plot them. Further functions are included that are intended for didactic use. The package implements, and extends, methods described in J.H. Maindonald and C.J. Burden (2005) <https://journal.austms.org.au/V46/CTAC2004/Main/home.html>.
Version: | 0.59-2 |
Depends: | R (≥ 3.0.0) |
Imports: | MASS, multtest |
Suggests: | knitr |
Published: | 2023-09-14 |
DOI: | 10.32614/CRAN.package.hddplot |
Author: | John Maindonald |
Maintainer: | John Maindonald <jhmaindonald at gmail.com> |
License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
URL: | https://github.com/jhmaindonald/hddplot |
NeedsCompilation: | no |
Citation: | hddplot citation info |
Materials: | README |
CRAN checks: | hddplot results |
Reference manual: | hddplot.pdf |
Vignettes: |
Feature Selection Bias in Classification of High Dimensional Data |
Package source: | hddplot_0.59-2.tar.gz |
Windows binaries: | r-devel: hddplot_0.59-2.zip, r-release: hddplot_0.59-2.zip, r-oldrel: hddplot_0.59-2.zip |
macOS binaries: | r-release (arm64): hddplot_0.59-2.tgz, r-oldrel (arm64): hddplot_0.59-2.tgz, r-release (x86_64): hddplot_0.59-2.tgz, r-oldrel (x86_64): hddplot_0.59-2.tgz |
Old sources: | hddplot archive |
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