Bayesian Cluster Validity Index
BCVI-Correlation Cluster Validity (CCV) index
BCVI-Calinski–Harabasz (CH) index
BCVI-Chou-Su-Lai (CSL) index
BCVI-Davies–Bouldin (DB) and DB* (DBs) indexes
BCVI-Dunn index (DI)
BCVI-The generalized C (GC) index
BCVI-HF index
BCVI-Modified Kernel form of Pakhira-Bandyopadhyay-Maulik (KPBM) index
BCVI-KWON index
BCVI-KWON2 index
BCVI-Point biserial correlation (PB)
BCVI-Pakhira-Bandyopadhyay-Maulik (PBM) index
BCVI-The score function
BCVI-Starczewski and Pakhira-Bandyopadhyay-Maulik for crisp clustering...
BCVI-Tang index
BCVI-Wu and Li (WL) index
BCVI-Wiroonsri and Preedasawakul (WP) index
BCVI-Wiroonsri (WI) index
BCVI-Xie and Beni (XB) index
Bayesian cluster validity index
Plots for visualizing BCVI
Algorithms for computing and generating plots with and without error bars for Bayesian cluster validity index (BCVI) (O. Preedasawakul, and N. Wiroonsri, A Bayesian Cluster Validity Index, Computational Statistics & Data Analysis, 202, 108053, 2025. <doi:10.1016/j.csda.2024.108053>) based on several underlying cluster validity indexes (CVIs) including Calinski-Harabasz, Chou-Su-Lai, Davies-Bouldin, Dunn, Pakhira-Bandyopadhyay-Maulik, Point biserial correlation, the score function, Starczewski, and Wiroonsri indices for hard clustering, and Correlation Cluster Validity, the generalized C, HF, KWON, KWON2, Modified Pakhira-Bandyopadhyay-Maulik, Pakhira-Bandyopadhyay-Maulik, Tang, Wiroonsri-Preedasawakul, Wu-Li, and Xie-Beni indices for soft clustering. The package is compatible with K-means, fuzzy C means, EM clustering, and hierarchical clustering (single, average, and complete linkage). Though BCVI is compatible with any underlying existing CVIs, we recommend users to use either WI or WP as the underlying CVI.