Package: KernelKnn 1.1.6
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.
Authors:
KernelKnn_1.1.6.tar.gz
KernelKnn_1.1.6.zip(r-4.7)KernelKnn_1.1.6.zip(r-4.6)KernelKnn_1.1.6.zip(r-4.5)
KernelKnn_1.1.6.tgz(r-4.6-x86_64)KernelKnn_1.1.6.tgz(r-4.6-arm64)KernelKnn_1.1.6.tgz(r-4.5-x86_64)KernelKnn_1.1.6.tgz(r-4.5-arm64)
KernelKnn_1.1.6.tar.gz(r-4.7-arm64)KernelKnn_1.1.6.tar.gz(r-4.7-x86_64)KernelKnn_1.1.6.tar.gz(r-4.6-arm64)KernelKnn_1.1.6.tar.gz(r-4.6-x86_64)
KernelKnn_1.1.6.tgz(r-4.6-emscripten)
manual.pdf |manual.html✨
card.svg |card.png
KernelKnn/json (API)
NEWS
| # Install 'KernelKnn' in R: |
| install.packages('KernelKnn', repos = c('https://mlampros.r-universe.dev', 'https://cloud.r-project.org')) |
Bug tracker:https://github.com/mlampros/kernelknn/issues
Pkgdown/docs site:https://mlampros.github.io
- Boston - Boston Housing Data
- ionosphere - Johns Hopkins University Ionosphere database
cpp11distance-metrickernel-methodsknnrcpparmadilloopenblascppopenmp
Last updated from:d179a72858. Checks:11 NOTE, 2 OK. Indexed: yes.
| Target | Result | Time | Files | Syslog |
|---|---|---|---|---|
| linux-devel-arm64 | NOTE | 181 | ||
| linux-devel-x86_64 | NOTE | 148 | ||
| source / vignettes | OK | 281 | ||
| linux-release-arm64 | NOTE | 135 | ||
| linux-release-x86_64 | NOTE | 140 | ||
| macos-release-arm64 | NOTE | 88 | ||
| macos-release-x86_64 | NOTE | 218 | ||
| macos-oldrel-arm64 | NOTE | 102 | ||
| macos-oldrel-x86_64 | NOTE | 304 | ||
| windows-devel | NOTE | 147 | ||
| windows-release | NOTE | 134 | ||
| windows-oldrel | NOTE | 112 | ||
| wasm-release | OK | 106 |
Exports:distMat.KernelKnndistMat.knn.index.distKernelKnnKernelKnnCVknn.index.dist
Dependencies:RcppRcppArmadillo
binary classification using the ionosphere data
Rendered frombinary_classification_using_the_ionosphere_data.Rmdusingknitr::rmarkdownon May 28 2026.Last update: 2017-10-30
Started: 2016-07-10
Image classification of the MNIST and CIFAR-10 data using KernelKnn and HOG (histogram of oriented gradients)
Rendered fromimage_classification_using_MNIST_CIFAR_data.Rmdusingknitr::rmarkdownon May 28 2026.Last update: 2016-09-08
Started: 2016-07-10
Regression using the Housing data
Rendered fromregression_using_the_housing_data.Rmdusingknitr::rmarkdownon May 28 2026.Last update: 2017-10-30
Started: 2016-07-10
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Boston Housing Data (Regression) | Boston |
| kernel k-nearest-neighbors using a distance matrix | distMat.KernelKnn |
| indices and distances of k-nearest-neighbors using a distance matrix | distMat.knn.index.dist |
| Johns Hopkins University Ionosphere database (binary classification) | ionosphere |
| kernel k-nearest-neighbors | KernelKnn |
| kernel-k-nearest-neighbors using cross-validation | KernelKnnCV |
| indices and distances of k-nearest-neighbors | knn.index.dist |
