KernelKnn: Kernel k Nearest Neighbors

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: 1.1.5
Depends: R (≥ 2.10.0)
Imports: Rcpp (≥ 0.12.5)
LinkingTo: Rcpp, RcppArmadillo
Suggests: testthat, covr, knitr, rmarkdown
Published: 2023-01-06
DOI: 10.32614/CRAN.package.KernelKnn
Author: Lampros Mouselimis ORCID iD [aut, cre], Matthew Parks [ctb] (Github Contributor)
Maintainer: Lampros Mouselimis <mouselimislampros at>
License: MIT + file LICENSE
NeedsCompilation: yes
SystemRequirements: libarmadillo: apt-get install -y libarmadillo-dev (deb), libblas: apt-get install -y libblas-dev (deb), liblapack: apt-get install -y liblapack-dev (deb), libarpack++2: apt-get install -y libarpack++2-dev (deb), gfortran: apt-get install -y gfortran (deb)
Citation: KernelKnn citation info
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_1.1.5.tar.gz
Windows binaries: r-devel:, r-release:, r-oldrel:
macOS binaries: r-release (arm64): KernelKnn_1.1.5.tgz, r-oldrel (arm64): KernelKnn_1.1.5.tgz, r-release (x86_64): KernelKnn_1.1.5.tgz, r-oldrel (x86_64): KernelKnn_1.1.5.tgz
Old sources: KernelKnn archive

Reverse dependencies:

Reverse depends: elmNNRcpp
Reverse imports: demuxSNP, imbalance, nmslibR, RaSEn, scMultiSim
Reverse suggests: SuperLearner, superMICE


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