(simple) Tool for estimating the number of clusters

12 validity indices, illustrate estimation of the number of clusters
Updated 8 Jul 2009

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For validation of clustering results in cluster analysis, it is important to use some objective measures to evaluate the clustering quality. This tool provides programs of such validity indices, including 4 External validity indices and 8 Internal validity indices: Rand index, Adjusted Rand index, Silhouette, Calinski-Harabasz, Davies-Bouldin, Homogeneity, Separation, and etc.

This tool is suitable for the performance comparison of different indices on the estimation of the number of clusters, algorithm design for applications by using or improving part codes, and etc.

Cite As

Kaijun Wang (2024). (simple) Tool for estimating the number of clusters (https://www.mathworks.com/matlabcentral/fileexchange/13916-simple-tool-for-estimating-the-number-of-clusters), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2006a
Compatible with any release
Platform Compatibility
Windows macOS Linux

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Version Published Release Notes

new release (Version 2.0)

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