slugReview Paper on Clustering and Validation Techniques

Apply

slugReview Paper on Clustering and Validation Techniques

Journal Title: International Journal for Research in Applied Science and Engineering Technology (IJRASET) - Year 2014, Vol 2, Issue 5

Abstract

Clustering is important in data analysis and data mining applications. It is the task of grouping a set of objects so that objects in the same group are more similar to each other than to those in other groups (clusters). The overall goal of the data mining process is to extract information from a large data set and transform it into an understandable form for further use. Clustering can be done by the different no. of algorithms such as hierarchical, partitioning, grid and density based algorithms. Hierarchical clustering is the connectivity based clustering. Partitioning is the centroid based clustering, the value of k - mean is set. Clustering has been applied to serve various purposes like, to gain insight to data distribution, generate hypotheses, to observe the characteristic and find anomalies. The intension of this paper is to provide a categorization of some well known clustering algorithms. It also describes the clustering process and overview of the different clustering methods. The validation of clustering structures is the most difficult and frustrating part of cluster analysis. Validation comparing the results of two clusters and find out the best cluster.

Authors and Affiliations

Jyoti, Neha Kaushik, Rekha

Keywords

EP ID EP18078
DOI -
Views 308
Downloads 11