Ecosyste.ms: Awesome
An open API service indexing awesome lists of open source software.
https://github.com/klausvigo/kknn
Weighted k-Nearest Neighbors
https://github.com/klausvigo/kknn
nearest-neighbor r
Last synced: 2 days ago
JSON representation
Weighted k-Nearest Neighbors
- Host: GitHub
- URL: https://github.com/klausvigo/kknn
- Owner: KlausVigo
- Created: 2015-04-19T19:55:10.000Z (over 9 years ago)
- Default Branch: master
- Last Pushed: 2021-05-31T12:43:29.000Z (over 3 years ago)
- Last Synced: 2024-08-06T03:05:13.185Z (3 months ago)
- Topics: nearest-neighbor, r
- Language: R
- Homepage: http://klausvigo.github.io/kknn/
- Size: 1.04 MB
- Stars: 23
- Watchers: 5
- Forks: 10
- Open Issues: 15
-
Metadata Files:
- Readme: README.md
Awesome Lists containing this project
README
[![R-CMD-check](https://github.com/KlausVigo/kknn/workflows/R-CMD-check/badge.svg)](https://github.com/KlausVigo/kknn/actions)
[![CRAN Status Badge](http://www.r-pkg.org/badges/version/kknn)](https://cran.r-project.org/package=kknn)
[![License](http://img.shields.io/badge/license-GPL%20%28%3E=%202%29-brightgreen.svg?style=flat)](http://www.gnu.org/licenses/gpl-2.0.html)
[![CRAN Downloads](http://cranlogs.r-pkg.org/badges/kknn)](https://cran.r-project.org/package=kknn)
[![Research software impact](http://depsy.org/api/package/cran/kknn/badge.svg)](http://depsy.org/package/r/kknn)
[![codecov](https://codecov.io/gh/KlausVigo/kknn/branch/master/graph/badge.svg)](https://codecov.io/gh/KlausVigo/kknn)
[![Coverage Status](https://coveralls.io/repos/github/KlausVigo/kknn/badge.svg?branch=master)](https://coveralls.io/github/KlausVigo/kknn?branch=master)kknn
========================================================kknn is a R package for Weighted k-Nearest Neighbors Classification, Regression and Clustering.
You can install
- the latest released version `install.packages("kknn")`
- the latest development version `devtools::install_github("KlausVigo/kknn")`If you use kknn please cite:
[Hechenbichler K. and Schliep K.P. (2004) Weighted k-Nearest-Neighbor Techniques and Ordinal Classification, Discussion Paper 399, SFB 386, Ludwig-Maximilians University Munich](https://doi.org/10.5282/ubm/epub.1769)
License
-------
kknn is licensed under the GPLv2.