An Analysis of the Admissibility of the Objective Functions Applied in Evolutionary Multi-objective Clustering

Autor: Morimoto, Cristina Y., Pozo, Aurora, de Souto, Marcílio C. P.

A variety of clustering criteria has been applied as an objective function in Evolutionary Multi-Objective Clustering approaches (EMOCs). However, most EMOCs do not provide detailed analysis regarding the choice and usage of the objective functions.

Externí odkaz: http://arxiv.org/abs/2206.09483

Multi-objective Clustering: A Data-driven Analysis of MOCLE, MOCK and $\Delta$-MOCK

Autor: Kultzak, Adriano, Morimoto, Cristina Y., Pozo, Aurora, de Souto, Marcílio C. P.

We present a data-driven analysis of MOCK, $\Delta$-MOCK, and MOCLE. These are three closely related approaches that use multi-objective optimization for crisp clustering. More specifically, based on a collection of 12 datasets presenting different p

Externí odkaz: http://arxiv.org/abs/2110.07521

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Turing's analysis of computation and artificial neural networks.

Autor: de Oliveira, Wilson R.¹, de Souto, Marcílio C. P.², Ludermir, Teresa B.³

Publikováno v: Journal of Intelligent & Fuzzy Systems. 2002/2003, Vol. 13 Issue 2-4, p85-98. 14p.

Impact of Base Partitions on Multi-objective and Traditional Ensemble Clustering Algorithms.

Autor: Piantoni, Jane, Faceli, Katti, Sakata, Tiemi C., Pereira, Julio C., de Souto, Marcílio C. P.

Publikováno v: Neural Information Processing: 22nd International Conference, ICONIP 2015, Istanbul, Turkey, November 9-12, 2015, Proceedings, Part I; 2015, p696-704, 9p