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Article

A General Framework for Mixed and Incomplete Data Clustering Based on Swarm Intelligence Algorithms

1
CIDETEC, Instituto Politécnico Nacional, Av. Juan de Dios Bátiz s/n, Nueva Industrial Vallejo, GAM, CDMX 07700, Mexico
2
Facultad de Ciencias Informáticas, Universidad de Ciego de Ávila, Modesto Reyes 65100, Cuba
3
CIC, Instituto Politécnico Nacional, Av. Juan de Dios Bátiz s/n, Nueva Industrial Vallejo, GAM, CDMX 07738, Mexico
*
Authors to whom correspondence should be addressed.
Academic Editor: Yong-Hyuk Kim
Mathematics 2021, 9(7), 786; https://doi.org/10.3390/math9070786
Received: 16 February 2021 / Revised: 17 March 2021 / Accepted: 25 March 2021 / Published: 6 April 2021
(This article belongs to the Special Issue Swarm and Evolutionary Computation—Bridging Theory and Practice)
Swarm intelligence has appeared as an active field for solving numerous machine-learning tasks. In this paper, we address the problem of clustering data with missing values, where the patterns are described by mixed (or hybrid) features. We introduce a generic modification to three swarm intelligence algorithms (Artificial Bee Colony, Firefly Algorithm, and Novel Bat Algorithm). We experimentally obtain the adequate values of the parameters for these three modified algorithms, with the purpose of applying them in the clustering task. We also provide an unbiased comparison among several metaheuristics based clustering algorithms, concluding that the clusters obtained by our proposals are highly representative of the “natural structure” of data. View Full-Text
Keywords: clustering; mixed and incomplete data; artificial bee colony; firefly algorithm; novel bat algorithm clustering; mixed and incomplete data; artificial bee colony; firefly algorithm; novel bat algorithm
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MDPI and ACS Style

Villuendas-Rey, Y.; Barroso-Cubas, E.; Camacho-Nieto, O.; Yáñez-Márquez, C. A General Framework for Mixed and Incomplete Data Clustering Based on Swarm Intelligence Algorithms. Mathematics 2021, 9, 786. https://doi.org/10.3390/math9070786

AMA Style

Villuendas-Rey Y, Barroso-Cubas E, Camacho-Nieto O, Yáñez-Márquez C. A General Framework for Mixed and Incomplete Data Clustering Based on Swarm Intelligence Algorithms. Mathematics. 2021; 9(7):786. https://doi.org/10.3390/math9070786

Chicago/Turabian Style

Villuendas-Rey, Yenny, Eley Barroso-Cubas, Oscar Camacho-Nieto, and Cornelio Yáñez-Márquez. 2021. "A General Framework for Mixed and Incomplete Data Clustering Based on Swarm Intelligence Algorithms" Mathematics 9, no. 7: 786. https://doi.org/10.3390/math9070786

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