Normal Mixture Model-Based Clustering of Data Using Genetic Algorithm
| Autor: | Maruf Gogebakan, Hamza Erol |
|---|---|
| Rok vydání: | 2020 |
| Předmět: |
0209 industrial biotechnology
Multivariate statistics business.industry Computer science Pattern recognition 02 engineering and technology Center (group theory) Mixture model ComputingMethodologies_PATTERNRECOGNITION 020901 industrial engineering & automation Genetic algorithm 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Artificial intelligence business Cluster analysis |
| Zdroj: | Artificial Intelligence and Applied Mathematics in Engineering Problems ISBN: 9783030361778 |
| DOI: | 10.1007/978-3-030-36178-5_43 |
| Popis: | In this study, a new algorithm was developed for clustering multivariate big data. Normal mixture distributions are used to determine the partitions of variables. Normal mixture models obtained from the partitions of variables are generated using Genetic Algorithms (GA). Each partition in the variables corresponds to a clustering center in the normal mixture model. The best model that fits the data structure from normal mixture models is obtained by using the information criteria obtained from normal mixture distributions. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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