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.
Kaijun Wang (2021). (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 .
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