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odetector
View on CRAN: Click
here
Download and install odetector package within the R console
Install from CRAN:
install.packages("odetector")
Install from Github:
library("remotes")
install_github("cran/odetector")
Install by package version:
library("remotes")
install_version("odetector", "1.0.1")
Attach the package and use:
library("odetector")
Maintained by
Zeynel Cebeci
[Scholar Profile | Author Map]
[Scholar Profile | Author Map]
All associated links for this package
First Published: 2022-10-04
Latest Update: 2022-11-08
Description:
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 ). 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.
How to cite:
Zeynel Cebeci (2022). odetector: Outlier Detection Using Partitioning Clustering Algorithms. R package version 1.0.1, https://cran.r-project.org/web/packages/odetector
Previous versions and publish date:
1.0.0 (2022-10-04 09:50)
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Other R packages that odetector depends,
imports, suggests or enhances
Functions, R codes and Examples using
the odetector R package
Some associated functions: detect.outliers . odetector-package . pairs.outliers . plot.outliers . print.outliers . remove.outliers . summary.outliers . x3p4c .
Some associated R codes: detect.outliers.R . pairs.outliers.R . plot.outliers.R . print.outliers.R . remove.outliers.R . summary.outliers.R . Full odetector package functions and examples
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