Identify Best Similarity Matrix to Find Accurate Cluster Using Dendrogram Distance

Data Mining has several techniques clustering is one of them. Clustering techniques are used in several real life applications like artificial intelligence, pattern recognition, economics, ecology, psychiatry and marketing. There are several algorithms and methods have been developed to improve clustering process. There are several issue like cluster size, depth, number of cluster, Breadth, and relation between object are consider for a clustering method. There are several new methods and techniques have been proposed by various researchers to improve the clustering process in term of accuracy and scalability. In this paper we proposed new concepts based on dendrogram distance to identify the correct distance matrix to find more accurate cluster. The Proposed approach provides which clustering techniques are suitable for a particular data.