Package: kpeaks 1.1.0
Zeynel Cebeci
kpeaks: Determination of K Using Peak Counts of Features for Clustering
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.
Authors:
kpeaks_1.1.0.tar.gz
kpeaks_1.1.0.tar.gz(r-4.5-noble)kpeaks_1.1.0.tar.gz(r-4.4-noble)
kpeaks_1.1.0.tgz(r-4.4-emscripten)kpeaks_1.1.0.tgz(r-4.3-emscripten)
kpeaks.pdf |kpeaks.html✨
kpeaks/json (API)
NEWS
| # Install 'kpeaks' in R: |
| install.packages('kpeaks', repos = c('https://cran.r-universe.dev', 'https://cloud.r-project.org')) |
- x5p4c - Synthetic Data Set contains 5 Variables and 4 Clusters
This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.
Last updated 5 years agofrom:7cb2c9bfdd. Checks:OK: 2. Indexed: yes.
| Target | Result | Date |
|---|---|---|
| Doc / Vignettes | OK | Nov 06 2024 |
| R-4.5-linux | OK | Nov 06 2024 |
Exports:findkfindpolypeaksgenpolygonplotpolygonrmshoulders
Dependencies:
Readme and manuals
Help Manual
| Help page | Topics |
|---|---|
| Determination of K Using Peak Counts of Features for Clustering | kpeaks-package |
| Estimate the Number of Clusters in a Data Set | findk |
| Find the Peaks of a Frequency Polygon | findpolypeaks |
| Generate the Classes to Build a Frequency Polygon | genpolygon |
| Plot Frequency Polygons | plotpolygon |
| Shoulders Removal in Frequency Polygons | rmshoulders |
| Synthetic Data Set contains 5 Variables and 4 Clusters | x5p4c |