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fuzzy-cluster-validity-index

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sayboud / UniversalCVI

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Algorithms for checking the accuracy of a clustering result with known classes, computing cluster validity indices, and generating plots for comparing them. The package is compatible with K-means, fuzzy C means, EM clustering, and hierarchical clustering (single, average, and complete linkage).

python machine-learning clustering scikit-learn statistical-learning silhouette k-means unsupervised-learning em-algorithm fuzzy-cmeans-clustering hierarchical-clustering cluster-validity-index fuzzy-clustering gaussian-mixture clustering-analysis dunnindex cluster-validation fuzzy-cluster-validity-index calinski-harabasz-index davies-bouldin-index
  • Updated Jun 22, 2026
  • Python

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