Literature Survey On Clustering Techniques

Abstract

Clustering is the assignment of data objects (records) into groups (called clusters) so that data objects from the same cluster are more similar to each other than objects from different clusters. Clustering techniques have been discussed extensively in similarity search, Segmentation, Statistics ,Machine Learning ,Trend Analysis, Pattern Recognition and classification. Clustering methods can be classified in to i)partition methods2)Hierarchical methods,3)Density Based methods 4)Grid based methods5)Model Based methods. in this paper, i would like to give review about clustering methods by taking some example for each classification. I am also providing comparative statement by taking constraints i.e Data type, Cluster Shape, Complexity, Data Set, Measure, Advantages and Disadvantages.