Optimization of K-means clustering using genetic algorithm

摘要

Clustering is regarded as a process that organize objects into groups where members are similar and the process help in arranging objects and finding similar patterns. The main idea behind the work is to minimize the steps of iteration for clustering the data so that desired information can be obtained in lesser amount of time. The methodology being employed is genetic algorithm which reduces the number of steps. It has been found out that by using GA the steps are reduced with respect to normal k-means technique. In future the technique can be employed by using other evolutionary techniques like DE, PSO, ACO.