CLAMS: A System for Zero-Shot Model Selection for Clustering

• URL: http://arxiv.org/abs/2407.11286v1
• Date: Mon, 15 Jul 2024 23:50:07 GMT
• Title: CLAMS: A System for Zero-Shot Model Selection for Clustering
• Authors: Prabhant Singh, Pieter Gijsbers, Murat Onur Yildirim, Elif Ceren Gok, Joaquin Vanschoren,
• Abstract summary: We propose an AutoML system that enables model selection on clustering problems by leveraging optimal transport-based dataset similarity. We compare our results against multiple clustering baselines and find that it outperforms all of them, hence demonstrating the utility of similarity-based automated model selection for solving clustering applications.
• Score: 3.7127285734321194
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: We propose an AutoML system that enables model selection on clustering problems by leveraging optimal transport-based dataset similarity. Our objective is to establish a comprehensive AutoML pipeline for clustering problems and provide recommendations for selecting the most suitable algorithms, thus opening up a new area of AutoML beyond the traditional supervised learning settings. We compare our results against multiple clustering baselines and find that it outperforms all of them, hence demonstrating the utility of similarity-based automated model selection for solving clustering applications.

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