Hybrid K-means Algorithm and Genetic Algorithm for Cluster Analysis

Dianhu Cheng, Xiangqian Ding, Jianxin Zeng, Ning Yang

Abstract


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.

 

DOI : http://dx.doi.org/10.11591/telkomnika.v12i4.4805


Keywords


Cluster analysis, K-means Algorithm, Genetic Algorithm, cluster number, time consuming

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Indonesian Journal of Electrical Engineering and Computer Science (IJEECS)
p-ISSN: 2502-4752, e-ISSN: 2502-4760
This journal is published by the Institute of Advanced Engineering and Science (IAES) in collaboration with Intelektual Pustaka Media Utama (IPMU).

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