Cluster validation is an important and necessary step in cluster analysis. This visual cluster validation tool CVAP based on GUI provides important tools and convenient analysis environment for validity evaluation of clustering solutions, estimation of the number of clusters and performance comparison between candidate clustering algorithms.
CVAP includes 4 External validity indices, 14 Internal validity indices and 5 clustering algorithms (K-means, PAM, hierarchical clustering and etc.). It supports other clustering algorithms via loading a solution file with class labels, or by adding new codes. And similarity metrics of Euclidean distance and Pearson correlation coefficient are supported.
Some useful information and references are in help files "Readme.txt", please read them first.
Kaijun Wang (2022). CVAP: Cluster Validity Analysis Platform (cluster analysis and validation tool) (https://www.mathworks.com/matlabcentral/fileexchange/14620-cvap-cluster-validity-analysis-platform-cluster-analysis-and-validation-tool), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform CompatibilityWindows macOS Linux
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