Extends the simple k-nearest neighbors algorithm by incorporating numerous kernel functions and a variety of distance metrics. The package takes advantage of 'RcppArmadillo' to speed up the calculation of distances between observations.
| Version: | 1.0.8 |
| Depends: | R (≥ 2.10.0) |
| Imports: | Rcpp (≥ 0.12.5) |
| LinkingTo: | Rcpp, RcppArmadillo |
| Suggests: | testthat, covr, knitr, rmarkdown |
| Published: | 2018-01-16 |
| Author: | Lampros Mouselimis |
| Maintainer: | Lampros Mouselimis <mouselimislampros at gmail.com> |
| BugReports: | https://github.com/mlampros/KernelKnn/issues |
| License: | MIT + file LICENSE |
| URL: | https://github.com/mlampros/KernelKnn |
| NeedsCompilation: | yes |
| Materials: | README NEWS |
| CRAN checks: | KernelKnn results |
| Reference manual: | KernelKnn.pdf |
| Vignettes: |
binary classification using the ionosphere data Image classification of the MNIST and CIFAR-10 data using KernelKnn and HOG (histogram of oriented gradients) Regression using the Housing data |
| Package source: | KernelKnn_1.0.8.tar.gz |
| Windows binaries: | r-devel: KernelKnn_1.0.8.zip, r-release: KernelKnn_1.0.8.zip, r-oldrel: KernelKnn_1.0.8.zip |
| OS X binaries: | r-release: KernelKnn_1.0.8.tgz, r-oldrel: KernelKnn_1.0.8.tgz |
| Old sources: | KernelKnn archive |
| Reverse depends: | elmNNRcpp |
| Reverse imports: | imbalance, nmslibR |
| Reverse suggests: | SuperLearner |
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