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kknn: Weighted k-Nearest Neighbors

Weighted k-Nearest Neighbors for Classification, Regression and Clustering.

Version: 1.3.1
Depends: R (≥ 2.10)
Imports: igraph (≥ 1.0), Matrix, stats, graphics
Published: 2016-03-26
Author: Klaus Schliep [aut, cre], Klaus Hechenbichler [aut], Antoine Lizee [ctb]
Maintainer: Klaus Schliep <klaus.schliep at gmail.com>
License: GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
URL: https://github.com/KlausVigo/kknn
NeedsCompilation: yes
Materials: README NEWS
CRAN checks: kknn results

Documentation:

Reference manual: kknn.pdf

Downloads:

Package source: kknn_1.3.1.tar.gz
Windows binaries: r-devel: kknn_1.3.1.zip, r-release: kknn_1.3.1.zip, r-oldrel: kknn_1.3.1.zip
macOS binaries: r-release (arm64): kknn_1.3.1.tgz, r-oldrel (arm64): kknn_1.3.1.tgz, r-release (x86_64): kknn_1.3.1.tgz, r-oldrel (x86_64): kknn_1.3.1.tgz
Old sources: kknn archive

Reverse dependencies:

Reverse depends: EnsembleBase
Reverse imports: aRtsy, DaMiRseq, jrSiCKLSNMF, OptiSembleForecasting, pheble, rgnoisefilt, rminer, RSDA, signeR, swfscMisc, traineR, viraldomain, viralmodels, viralx
Reverse suggests: butcher, finetune, flowml, fscaret, GenericML, healthyR.ai, MachineShop, mlr, mlr3learners, mlr3pipelines, mlr3tuningspaces, mlrMBO, parsnip, sense, SSLR, stacks, tidyAML, tune, utiml, workflowsets

Linking:

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These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.
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