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odetector

1.0.1

Outlier Detection Using Partitioning Clustering Algorithms

0packages depend
2.2Kdownloads / year
test coverage
11/13checks pass

Overview

About
Maintained by Zeynel CebeciFirst published 2022-10-042 releasesCRAN page ↗GitHub ↗

An object is called "outlier" if it remarkably deviates from the other objects in a data set. Outlier detection is the process to find outliers by using the methods that are based on distance measures, clustering and spatial methods (Ben-Gal, 2005 <ISBN 0-387-24435-2>). It is one of the intensively studied research topics for identification of novelties, frauds, anomalies, deviations or exceptions in addition to its use for outlier removing in data processing. This package provides the implementations of some novel approaches to detect the outliers based on typicality degrees that are obtained with the soft partitioning clustering algorithms such as Fuzzy C-means and its variants.

Install

Health

CRAN checks
2NOTE11OK
Failing flavors
  • NOTE r-devel-linux-x86_64-debian-clang
  • NOTE r-devel-linux-x86_64-debian-gcc
Slowest check: 1.4 min · r-devel-windows-x86_64
Code health
None
Tests · ratio 0.00
not tracked
Coverage
4
Dependencies · direct
Check history
  • NOTE2026-03-10
    12 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE

Documentation

Documentation
READMENoVignettesYes · dynamicpkgdown siteNoNEWSNoCode of conductNoContributing guideNo
Examples that run
100%
Documented parameters
not tracked
Return-value docs
not tracked
References docs
38%

Downloads

2.2K
CRAN downloads in the past year
Rank #18,785 · ~6/day · ~180/mo
Daily download trend is not available in this view yet.
14730 days
58190 days
2.2K1 year
Compare downloads with other packages →
Also on119 r2u17 autocran

Repository

Repository
0Stars
0Forks
0Open issues
0Open PRs
0Releases
outlier-detectionoutliersoutlier-removalcluster-analysisfcmpcmpartitioningfuzzy-clustering
Last activity 2022-10-11

Repository practices

Upstream repositoryBeta

Checks run against github.com/zcebeci/odetector on 2026-08-16.

No development-tooling practices detected in the upstream repository.

How this is detected·Detection ruleset v1 (2026-07-18)

Dependencies

Declared dependencies
4 external dependencies (excludes base and recommended)
Depends (1)
R >= 3.0.0
Imports (4)
ppclustutilsgraphicsgrDevices
LinkingTo (0)
none
Enhances (0)
none
Reverse dependencies
0direct
0indirect

Nothing depends on this yet.

Code & Tests

People & History

People (3)
Maintainer (1)
Author, Maintainer
Authors (1)
Author, Maintainer
Contributors (2)
Contributor
Contributor
Package Timeline

2 releases. Pick two to compare their code metrics. R releases are shown for context.

  • R
    R 4.6.0 released · 2026-04-24
  • R
    R 4.5.0 released · 2025-04-11
  • R
    R 4.4.0 released · 2024-04-24
  • R
    R 4.3.0 released · 2023-04-21
  • 1.0.1Latest
    2022-11-08 · current release · diff ↗
  • 1.0.0
    2022-10-04
  • R
    R 4.2.0 released · 2022-04-22

Package metadata

First published
2022-10-04
Total releases
2 / 4 yrs
License
GPL (>= 2) OSI
Minimum R
≥ 3.0.0
Bundled data
3.1 KB / 2 files
Download size
191 KB
Installed size
not tracked yet
With dependencies
not tracked yet
Appears in task views

Cite

Cite this package

Run in R for the authors' preferred citation:

citation("odetector")
Cebeci, Z., Cebeci, C., & Tahtali, Y. (2022). odetector: Outlier Detection Using Partitioning Clustering Algorithms (Version 1.0.1) [Computer software]. https://doi.org/10.32614/CRAN.package.odetector

This is what citation() produces when a package has no citation file of its own. If it prints something else, use that.

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 odetector version 1.0.1 [Data set]. HJJB, LLC. Data release v2026-08-18. https://doi.org/10.5281/zenodo.21843040

From data release v2026-08-18, which the citation names so these numbers can be found later. More on citing and the projects behind them.

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