Automatic clustering by multi-objective genetic algorithm with numeric and categorical features

•We have developed a clustering algorithm for an unknown number of clusters by MOGA.•It works with continuous and categorical featured data sets.•It can work with data sets having missing values.•The final solution is selected by majority vote by all non-dominated solutions.•Context-sensitive and cl...

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Vydané v:	Expert systems with applications Ročník 137; s. 357 - 379
Hlavní autori:	Dutta, Dipankar, Sil, Jaya, Dutta, Paramartha
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	New York Elsevier Ltd 15.12.2019 Elsevier BV
Predmet:	Automatic clustering Centroids Clustering Data points Genetic algorithms Iterative methods Machine learning Multi-Objective Genetic Algorithm (MOGA) Multiple objective analysis Optimization Pareto approach Statistical test Statistical test Automatic clustering Multi-Objective Genetic Algorithm (MOGA) Pareto approach
ISSN:	0957-4174, 1873-6793
On-line prístup:	Získať plný text
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