Random knn classification and regression are implemented. Random knn based feature selection methods are also included. The approaches are mainly developed for high-dimensional data with small sample size.
| Version: | 1.2-1 |
| Depends: | R (≥ 2.14), gmp (≥ 0.5-5) |
| Suggests: | Hmisc, Biobase, genefilter, golubEsets, chemometrics |
| Published: | 2015-06-09 |
| Author: | Shengqiao Li |
| Maintainer: | Shengqiao Li <lishengqiao at yahoo.com> |
| License: | GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| NeedsCompilation: | yes |
| Materials: | ChangeLog |
| CRAN checks: | rknn results |
| Reference manual: | rknn.pdf |
| Package source: | rknn_1.2-1.tar.gz |
| Windows binaries: | r-devel: rknn_1.2-1.zip, r-release: rknn_1.2-1.zip, r-oldrel: rknn_1.2-1.zip |
| macOS binaries: | r-release: rknn_1.2-1.tgz, r-oldrel: rknn_1.2-1.tgz |
| Old sources: | rknn archive |
| Reverse suggests: | mlr |
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