Analysis of Various Clustering Algorithms

Data clustering is a process of putting similar data into groups. A clustering algorithm partitions a data set into several groups such that the similarity within a group is larger than among groups. This paper reviews four types of clustering techniques- k-Means Clustering, Farther first clustering, Density Based Clustering, Filtered clusterer. These clustering techniques are implemented and analyzed using a clustering tool WEKA. Performance of the 4 techniques are presented and compared.