An Intelligent Fuzzy Convex Hull based Clustering Approach

mining refers to the extraction of knowledge by analyzing the data from different perspectives and accumulates them to form an useful information which could help the decision makers to take appropriate decisions. Classification and clustering has been the two broad areas in data mining. As the classification is a supervised learning approach, the clustering is an unsupervised learning approach and hence can be performed without the supervision of the domain experts. The basic concept is to group the objects in such a way so that the similar objects are closer to each. In this paper, an approach is made by fusing the concept of convex hull with fuzziness parameter. Each boundary data point is validated for the convex hull property to form a cluster. The decision value depends on the membership value of the particular point. The points satisfying the convex hull property forms a cluster. The performance