Size Constrained Clustering With MILP Formulation

Clustering is one of the essential tools for data mining since it reveals the natural structures of the unlabeled data. Many clustering algorithms have been proposed in the last decades. However, few of them are designed to adapt prior knowledge that is available in many real applications, such as t...

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Veröffentlicht in:	IEEE access 2020, Vol.8, p.1587-1599
Hauptverfasser:	Tang, Wei, Yang, Yang, Zeng, Lanling, Zhan, Yongzhao
Format:	Artikel
Sprache:	eng
Schlagworte:	Algorithms Centroids Clustering Clustering algorithms Clustering methods Constraint modelling Data mining Indexes Integer programming Iterative methods linear program Linear programming Matrix methods mean squared error Mixed integer Partitioning algorithms size constraints Task analysis
Online-Zugang:	Volltext
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