A Comparative Analysis between K-mean and Y-means Algorithms in Fisher’s Iris Data Sets

V.Leela#1, K.Sakthi priya*2,R.Manikandan#3 #1M.tech VLSI Design, Department of Computing, SASTRA university,Thanjavur-613401,India. Email:[email protected] *2 M.tech VLSI Design, Department of Computing, SASTRA University,Thanjavur-613401,India. Email:[email protected] #3Senior Assistant Professor, Department of ICT,SASTRA University,Thanjavur-613401,India. Email:[email protected] ABSTRACT: Cluster analysis plays a vital role in various fields in order to group similar data from the available database. There are various clustering algorithm available in order to cluster the data but the entire algorithm are not suitable for all process .This paper mainly address with the comparative performance analysis of partition based k-mean and y-mean algorithm in Iris flower datasets. The experimental results of iris data set show that the Y-Means algorithm yields the best results in clustering and time complexity compared with k-Mean algorithm in little iteration time.