A Feature Extraction with Graph Based Clustering

Abstract

This paper presents a detailed study of different graph theoretic method i.e. clustering algorithm. A cluster is collection or group of data objects that are similar to each other with the same cluster object and not similar with other Cluster object. Also it is study on different feature selection algorithm. To overcome the limitations of existing algorithm. A feature selection may be related with both the efficiency and effectiveness point of view. FAST algorithm is proposed. Features are different cluster relatively independent. Clustering based strategy has high probability of producing a subset of important and independent features. To adopt the
efficiency of fast clustering feature selection algorithm. It creates efficient minimum spanning tree clustering method.