A General Framework for Mixed and Incomplete Data Clustering Based on Swarm Intelligence Algorithms
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 intelligenc...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-04-01
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| Series: | Mathematics |
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| Online Access: | https://www.mdpi.com/2227-7390/9/7/786 |
| _version_ | 1827695870692294656 |
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| author | Yenny Villuendas-Rey Eley Barroso-Cubas Oscar Camacho-Nieto Cornelio Yáñez-Márquez |
| author_facet | Yenny Villuendas-Rey Eley Barroso-Cubas Oscar Camacho-Nieto Cornelio Yáñez-Márquez |
| author_sort | Yenny Villuendas-Rey |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-10T12:35:06Z |
| format | Article |
| id | doaj.art-b21afbb725ac4e95b7f5a60b72145e9e |
| institution | Directory Open Access Journal |
| issn | 2227-7390 |
| language | English |
| last_indexed | 2024-03-10T12:35:06Z |
| publishDate | 2021-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Mathematics |
| spelling | doaj.art-b21afbb725ac4e95b7f5a60b72145e9e2023-11-21T14:19:49ZengMDPI AGMathematics2227-73902021-04-019778610.3390/math9070786A General Framework for Mixed and Incomplete Data Clustering Based on Swarm Intelligence AlgorithmsYenny Villuendas-Rey0Eley Barroso-Cubas1Oscar Camacho-Nieto2Cornelio Yáñez-Márquez3CIDETEC, Instituto Politécnico Nacional, Av. Juan de Dios Bátiz s/n, Nueva Industrial Vallejo, GAM, CDMX 07700, MexicoFacultad de Ciencias Informáticas, Universidad de Ciego de Ávila, Modesto Reyes 65100, CubaCIDETEC, Instituto Politécnico Nacional, Av. Juan de Dios Bátiz s/n, Nueva Industrial Vallejo, GAM, CDMX 07700, MexicoCIC, Instituto Politécnico Nacional, Av. Juan de Dios Bátiz s/n, Nueva Industrial Vallejo, GAM, CDMX 07738, MexicoSwarm 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.https://www.mdpi.com/2227-7390/9/7/786clusteringmixed and incomplete dataartificial bee colonyfirefly algorithmnovel bat algorithm |
| spellingShingle | Yenny Villuendas-Rey Eley Barroso-Cubas Oscar Camacho-Nieto Cornelio Yáñez-Márquez A General Framework for Mixed and Incomplete Data Clustering Based on Swarm Intelligence Algorithms Mathematics clustering mixed and incomplete data artificial bee colony firefly algorithm novel bat algorithm |
| title | A General Framework for Mixed and Incomplete Data Clustering Based on Swarm Intelligence Algorithms |
| title_full | A General Framework for Mixed and Incomplete Data Clustering Based on Swarm Intelligence Algorithms |
| title_fullStr | A General Framework for Mixed and Incomplete Data Clustering Based on Swarm Intelligence Algorithms |
| title_full_unstemmed | A General Framework for Mixed and Incomplete Data Clustering Based on Swarm Intelligence Algorithms |
| title_short | A General Framework for Mixed and Incomplete Data Clustering Based on Swarm Intelligence Algorithms |
| title_sort | general framework for mixed and incomplete data clustering based on swarm intelligence algorithms |
| topic | clustering mixed and incomplete data artificial bee colony firefly algorithm novel bat algorithm |
| url | https://www.mdpi.com/2227-7390/9/7/786 |
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