AN EFFICIENT PRE CLUSTERING ALGORTHIM USING AN UNLABELLED DATA SETS

Abstract

Cluster analysis is one of the primary data analysis methods the type of Pre clustering algorthim used to estimate the no of clusters in unlabelled data sets. The Selection of the no of clusters is an important and challenging issue in cluster analysis. A no of attempts have been made to estimate no of clusters c in a given data sets. They attempt to choose the best partition from a set of alternative partitions. In contrast tendency assesement attempts to estimate c before clustering occursThe project focus on pre clustering tendency and determine the no of clusters in unlabeled data sets during cluster analysis by using proposed methodology Trusted Pre cluster Count Algorthim.