Package: kpeaks
Type: Package
Title: Determination of K Using Peak Counts of Features for Clustering
Version: 1.1.0
Date: 2020-02-08
Authors@R: c(person("Zeynel", "Cebeci", email = "zcebeci@cukurova.edu.tr", role = c("aut", "cre")), 
     person("Cagatay","Cebeci", role = "aut", email = "cagataycebeci@gmail.com"))
Author: Zeynel Cebeci [aut, cre],
  Cagatay Cebeci [aut]
Maintainer: Zeynel Cebeci <zcebeci@cukurova.edu.tr>
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.
Depends: R (>= 3.3.0)
License: GPL (>= 2)
LazyData: true
Imports: graphics, stats, utils, methods
NeedsCompilation: no
Packaged: 2020-02-08 16:20:22 UTC; user1
Repository: CRAN
Date/Publication: 2020-02-08 18:00:02 UTC
Built: R 4.6.0; ; 2026-04-25 19:40:54 UTC; unix
