arXiv Machine Learning By Mahdi Shamsi, Soosan Beheshti

Central Description Length (CDL) Clustering Validation Index

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arXiv:2606. 05230v1 Announce Type: cross Abstract: Selecting a clustering algorithm and its hyperparameters without labels is a common difficulty in engineering machine learning pipelines that work with unsupervised analysis of sensor, image, or process data.

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arXiv Machine Learning
Aug 28

Absolute indices for determining compactness, separability and number of clusters

The paper introduces absolute cluster indices that assess both compactness and separability of clusters, moving beyond relative measures commonly used in clustering validation. It defines a compactness function for each cluster and a set of neighboring points for cluster pairs to evaluate cluster quality and overall distribution margin. These indices are applied to determine the true number of clusters and are compared against widely-used validity indices on synthetic and real-world datasets.

By Adil M. Bagirov, Ramiz M. Aliguliyev, Nargiz Sultanova, Sona Taheri