Fixed-sized clusters $k$-Means

• URL: http://arxiv.org/abs/2501.16113v1
• Date: Mon, 27 Jan 2025 15:04:35 GMT
• Title: Fixed-sized clusters $k$-Means
• Authors: Mikko I. Malinen, Pasi Fränti,
• Abstract summary: A straightforward application is balanced clustering, where the sizes of each cluster are equal. In the $k$-means assignment phase, the algorithm solves an assignment problem using the Hungarian algorithm.
• Score: 1.7034813545878587
• License:
• Abstract: We present a $k$-means-based clustering algorithm, which optimizes the mean square error, for given cluster sizes. A straightforward application is balanced clustering, where the sizes of each cluster are equal. In the $k$-means assignment phase, the algorithm solves an assignment problem using the Hungarian algorithm. This makes the assignment phase time complexity $O(n^3)$. This enables clustering of datasets of size more than 5000 points.

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