Package: odetector 1.0.0

Zeynel Cebeci

odetector: Outlier Detection Using Partitioning Clustering Algorithms

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.

Authors:Zeynel Cebeci [aut, cre], Cagatay Cebeci [ctb], Yalcin Tahtali [ctb]

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NEWS

# Install 'odetector' in R:
install.packages('odetector', repos = c('https://zcebeci.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Bug tracker:https://github.com/zcebeci/odetector/issues

Datasets:
  • x3p4c - Synthetic data set consists of three variables with four clusters

On CRAN:

anomaly-detectioncluster-analysisclusteringclustering-methodsdatadatapreparationdatapreprocessingexception-handlingfcmfraud-detectionfuzzy-clusteringnovelty-detectionoutlier-detectionoutlier-removaloutlierspartitioningpcmsurprise-exploration

3.70 score 4 scripts 153 downloads 6 exports 6 dependencies

Last updated 2 years agofrom:745aec1790. Checks:OK: 7. Indexed: yes.

TargetResultDate
Doc / VignettesOKNov 09 2024
R-4.5-winOKNov 09 2024
R-4.5-linuxOKNov 09 2024
R-4.4-winOKNov 09 2024
R-4.4-macOKNov 09 2024
R-4.3-winOKNov 09 2024
R-4.3-macOKNov 09 2024

Exports:detect.outlierspairs.outliersplot.outliersprint.outliersremove.outlierssummary.outliers

Dependencies:inaparckpeakslhsMASSppclustRcpp

Outlier Detection Using Possibilistic and Fuzzy Clustering Algorithms

Rendered fromodetector.Rmdusingknitr::rmarkdownon Nov 09 2024.

Last update: 2022-10-04
Started: 2022-01-05