标题：An Efficient Numerical Methods for the Prediction of Clusters using K-means Algorithm with Bisection method for Comparing Uniform and Random Distribution Data Points
期刊名称：International Journal of Innovative Research in Computer and Communication Engineering
印刷版ISSN：2320-9798
电子版ISSN：2320-9801
出版年度：2013
卷号：1
期号：8
出版社：S&S Publications
摘要：In this paper we extract the cluster by using numerical as well as statistical methods for improvingefficiency using efficient algorithms of k-means in data mining. So, Data mining is defined as finding hiddeninformation in a database it has been called exploratory data analysis, data driven discovery, and deductive learning.[1]clustering is usually accomplished by determining the similarity among the data on predefined attributes. The mostsimilar data are grouped into clusters. This paper proposes a method for making the k-means algorithm and Bisectionmethod for more effective and efficient, so as to getting better cluster.
