Determining number and initial seeds of K-means clustring using GA

Abstract EN

Cluster analysis has been widely used in several disciplines, such as statistics, software engineering, biology, psychology and other social sciences, in order to identify natural groups in large amounts of data.

Clustering has also been widely adopted by researchers within computer science and especially the database community.

K-means is the most famous clustering algorithms.

But it suffering from some drawbacks which is the determining of number and initial seeds of clusters expected in the datasets.

In this paper we introduce ability of automatic clusters seeds and number detection technique using GA.