kfda
1.0.0Kernel Fisher Discriminant Analysis
Overview
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.
Install
Health
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- NOTE2026-03-100 OK · 14 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
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Code & Tests
- Cyclomatic complexity
- 1.0 median / 1 max
Test coverage
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Tests / Examples
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Functions
2 0 exported
Complexity
1 avg / 1 max
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2 nodes / 0 edges
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1 release. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- 1.0.0Latest2026-03-10 · current release
- RR 4.5.0 released · 2025-04-11
Package metadata
- First published
- 2017-09-27
- Total releases
- 1 / 9 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.0.0
- Download size
- 3.1 KB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet