Package: kfda 1.0.0

kfda: Kernel Fisher Discriminant Analysis

Kernel Fisher Discriminant Analysis (KFDA) is performed using Kernel Principal Component Analysis (KPCA) and Fisher Discriminant Analysis (FDA). There are some similar packages. First, 'lfda' is a package that performs Local Fisher Discriminant Analysis (LFDA) and performs other functions. In particular, 'lfda' seems to be impossible to test because it needs the label information of the data in the function argument. Also, the 'ks' package has a limited dimension, which makes it difficult to analyze properly. This package is a simple and practical package for KFDA based on the paper of Yang, J., Jin, Z., Yang, J. Y., Zhang, D., and Frangi, A. F. (2004) <doi:10.1016/j.patcog.2003.10.015>.

Authors:Donghwan Kim

kfda_1.0.0.tar.gz
kfda_1.0.0.zip(r-4.5)kfda_1.0.0.zip(r-4.4)kfda_1.0.0.zip(r-4.3)
kfda_1.0.0.tgz(r-4.4-any)kfda_1.0.0.tgz(r-4.3-any)
kfda_1.0.0.tar.gz(r-4.5-noble)kfda_1.0.0.tar.gz(r-4.4-noble)
kfda_1.0.0.tgz(r-4.4-emscripten)kfda_1.0.0.tgz(r-4.3-emscripten)
kfda.pdf |kfda.html
kfda/json (API)

# Install 'kfda' in R:
install.packages('kfda', repos = c('https://ainsuotain.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/ainsuotain/kfda/issues

On CRAN:

1.00 score 2 scripts 471 downloads 2 exports 2 dependencies

Last updated 7 years agofrom:62601662d7. Checks:OK: 3 NOTE: 4. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 16 2024
R-4.5-winNOTENov 16 2024
R-4.5-linuxNOTENov 16 2024
R-4.4-winNOTENov 16 2024
R-4.4-macNOTENov 16 2024
R-4.3-winOKNov 16 2024
R-4.3-macOKNov 16 2024

Exports:kfdakfda.predict

Dependencies:kernlabMASS