Package: kknn 1.4.1
kknn: Weighted k-Nearest Neighbors
Weighted k-Nearest Neighbors for Classification, Regression and Clustering.
Authors:
kknn_1.4.1.tar.gz
kknn_1.4.1.zip(r-4.7)kknn_1.4.1.zip(r-4.6)kknn_1.4.1.zip(r-4.5)
kknn_1.4.1.tgz(r-4.6-x86_64)kknn_1.4.1.tgz(r-4.6-arm64)kknn_1.4.1.tgz(r-4.5-x86_64)kknn_1.4.1.tgz(r-4.5-arm64)
kknn_1.4.1.tar.gz(r-4.7-arm64)kknn_1.4.1.tar.gz(r-4.7-x86_64)kknn_1.4.1.tar.gz(r-4.6-arm64)kknn_1.4.1.tar.gz(r-4.6-x86_64)
kknn_1.4.1.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
kknn/json (API)
NEWS
| # Install 'kknn' in R: |
| install.packages('kknn', repos = c('https://klausvigo.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/klausvigo/kknn/issues
- glass - Glass Identification Database
- ionosphere - Johns Hopkins University Ionosphere Database
- miete - Munich Rent Standard Database
Last updated from:61ebf7c521. Checks:13 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | OK | 128 | ||
| linux-devel-x86_64 | OK | 126 | ||
| source / vignettes | OK | 159 | ||
| linux-release-arm64 | OK | 141 | ||
| linux-release-x86_64 | OK | 138 | ||
| macos-release-arm64 | OK | 89 | ||
| macos-release-x86_64 | OK | 284 | ||
| macos-oldrel-arm64 | OK | 81 | ||
| macos-oldrel-x86_64 | OK | 246 | ||
| windows-devel | OK | 124 | ||
| windows-release | OK | 87 | ||
| windows-oldrel | OK | 81 | ||
| wasm-release | OK | 107 |
Exports:contr.dummycontr.metriccontr.ordinalcv.kknnkknnkknn.distspecClusttrain.kknn
Dependencies:clicpp11glueigraphlatticelifecyclemagrittrMatrixpkgconfigrlangvctrs
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Contrast Matrices | contr.dummy contr.metric contr.ordinal |
| Glass Identification Database | glass |
| Johns Hopkins University Ionosphere Database | ionosphere |
| Weighted k-Nearest Neighbor Classifier | kknn kknn.dist predict.kknn print.kknn summary.kknn |
| Munich Rent Standard Database (1994) | miete |
| Training kknn | cv.kknn plot.train.kknn predict.train.kknn print.train.kknn summary.train.kknn train.kknn |
| Spectral Clustering | plot.specClust specClust |
