Scrutiny of large datasets using clustering techniques

Abstract

Clustering technique is critically important step in data mining process. Clustering is a significant task in data analysis and data mining applications. It is the task of arrangement a set of objects so that objects in the identical group are more related to each other than to those in other groups (clusters). Data mining can do by passing through various phases. Mining can be done by using supervised and unsupervised learning. The clustering is unsupervised learning. A good clustering method will produce high superiority clusters with high intra-class similarity and low inter-class similarity. Its main distinctiveness is the fastest processing time. In this paper, an analysis of clustering and its different techniques in data mining is done. Results were quite encouraging and had shown high accuracy.