| Título: | Hybrid K-means Algorithm and Genetic Algorithm for Cluster Analysis |
| Autores: | Cheng, Dianhu; Ocean University of China |
| Fecha: | 2014-04-01 |
| Publicador: | TELKOMNIKA: Indonesian journal of electrical engineering |
| Fuente: |
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| Tipo: |
info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion |
| Tema: | Cluster analysis, K-means Algorithm, Genetic Algorithm, cluster number, time consuming |
| Descripción: | Cluster analysis isa fundamental technique for various filed such as pattern recognition, machinelearning and so forth. However, the cluster number is predefined by users inK-means algorithm, which is unpractical to implement. Since the number of clusters is a NP-completeproblem, Genetic Algorithm is employed to solve it. In addition, due to the largetime consuming in conventional method, an improved fitness function isproposed. According to the simulation results, the proposed approach isfeasible and effective. |
| Idioma: | No aplica |