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kpeaks  

Determination of K Using Peak Counts of Features for Clustering
View on CRAN: Click here


Download and install kpeaks package within the R console
Install from CRAN:
install.packages("kpeaks")

Install from Github:
library("remotes")
install_github("cran/kpeaks")

Install by package version:
library("remotes")
install_version("kpeaks", "1.1.0")



Attach the package and use:
library("kpeaks")
Maintained by
Zeynel Cebeci
[Scholar Profile | Author Map]
First Published: 2017-09-19
Latest Update: 2020-02-08
Description:
The number of clusters (k) is needed to start all the partitioning clustering algorithms. An optimal value of this input argument is widely determined by using some internal validity indices. Since most of the existing internal indices suggest a k value which is computed from the clustering results after several runs of a clustering algorithm they are computationally expensive. On the contrary, the package 'kpeaks' enables to estimate k before running any clustering algorithm. It is based on a simple novel technique using the descriptive statistics of peak counts of the features in a data set.
How to cite:
Zeynel Cebeci (2017). kpeaks: Determination of K Using Peak Counts of Features for Clustering. R package version 1.1.0, https://cran.r-project.org/web/packages/kpeaks. Accessed 01 Apr. 2025.
Previous versions and publish date:
0.1.0 (2017-09-19 11:37)
Other packages that cited kpeaks R package
View kpeaks citation profile
Other R packages that kpeaks depends, imports, suggests or enhances
Complete documentation for kpeaks
Functions, R codes and Examples using the kpeaks R package
Some associated functions: findk . findpolypeaks . genpolygon . kpeaks-package . plotpolygon . rmshoulders . x5p4c . 
Some associated R codes: kpeaks.R .  Full kpeaks package functions and examples
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