Optimization of K-Means clustering Using Genetic Algorithm

被引：0

作者：

Irfan, Shadab ^{[1
]}

Dwivedi, Gaurav ^{[2
]}

Ghosh, Subhajit ^{[1
]}

机构：

[1] Galgotias Univ Greater Noida, Greater Noida, Uttar Pradesh, India

[2] BIT Kanpur, Kanpur, Uttar Pradesh, India

来源：

2017 INTERNATIONAL CONFERENCE ON COMPUTING AND COMMUNICATION TECHNOLOGIES FOR SMART NATION (IC3TSN) | 2017年

关键词：

Clustering; k-means; Optimization; Genetic Algorithm;

D O I：

暂无

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

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 niethodolo* 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.

引用

页码：157 / 162

页数：6

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