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A Super K-Nearest Neighbor (SKNN) Classification Algorithm

0packages depend
2.8Kdownloads / year
–test coverage
13/13flavors OK

Overview

About

It's a Super K-Nearest Neighbor(SKNN) classification method with using kernel density to describe weight of the distance between a training observation and the testing sample. Comparison of performance between SKNN and KNN shows that SKNN is significantly superior to KNN.

Install

Health

CRAN checks
13OK
Slowest check: 1.0 min · r-oldrel-macos-x86_64
Status changes
  • OK13 OK2026-08-05
  • NOTE12 OK, 1 NOTE2026-08-01
  • OK14 OK2026-03-10
Advisories

none known

Documentation

In release 4.1.3
READMENoVignettesNoNEWSNoCitation fileNoWebsitenot declared in DESCRIPTION
Help pages
6includes a package overview page
Examples that run
100%5 run in a plain check
Exported functions with examples
75%
Documented parameters
100%
Return-value docs
100%
Help pages citing references
83%

Downloads

2.8K
CRAN downloads in the past year
Rank #22,303 · ~8/day · ~233/mo
Daily download trend is not available in this view yet.
23230 days
59790 days
2.8K1 year
Compare downloads with other packages →
Also on84 r2u2 autocran

Dependencies

Declared dependencies
0 external dependencies (excludes base and recommended)

Installing SKNN adds no packages beyond those that come with R.

Depends (2)
methodsstats
Imports (0)
none
LinkingTo (0)
none
Suggests (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

People & History

People (4)
Author, Maintainer since 1.0 (2021)
Contributor
Contributor · added in 2.0
Contributor
Listed in earlier versions (1)
Yi Ya
no longer listed · 1.0 to 4.0
Releases (9)

Pick two releases to compare their code metrics.

Package metadata

First published
2021-11-23
Total releases
9 / 5 yrs
License
GPL-2 OSI
Download size
4.3 KB

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("SKNN")
Yang, Y., Ebrahimi, N., Rubin, Y., & Zhang, J. (2026). SKNN: A Super K-Nearest Neighbor (SKNN) Classification Algorithm (Version 4.1.3) [Computer software]. https://doi.org/10.32614/CRAN.package.SKNN

This package has no citation file, so citation() returns this entry built from DESCRIPTION.

Cite the R Observatory

For a number measured here: a download total, a coverage figure, an archival date.

APA

Balamuta, J. J. (2026). R Observatory: Metrics for SKNN version 4.1.3 [Data set]. HJJB, LLC. Data release v2026-10-24. https://doi.org/10.5281/zenodo.21843040

From data release v2026-10-24, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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