Ground truth clustering is not the optimum clustering

Abstract Data clustering is a fundamental yet challenging task in data science. The minimum sum-of-squares clustering (MSSC) problem aims to partition data points into k clusters to minimize the sum of squared distances between the points and their cluster centers (centroids). Despite being NP-hard,...

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Hlavní autoři: Lucia Absalom Bautista, Timotej Hrga, Janez Povh, Shudian Zhao
Médium: Artigo
Jazyk:Inglês
Vydáno: Nature Portfolio 2025-03-01
Edice:Scientific Reports
Témata:
Minimum sum-of-squares clustering
Ground truth clustering
Extrinsic measures
Intrinsic measures
On-line přístup:https://doi.org/10.1038/s41598-025-90865-9
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