An Optimized repartitioned K-means Cluster algorithm using MapReduce Techniques for Big Data analysis
| Author(s) | : | T.Mohana Priya, Dr.A.Saradha |
| Institution | : | Research Scholar, Bharathiar University Coimbatore, Tamilnadu, Dr.SNS Rajalakshmi College of Arts and Science, Coimbatore |
| Published In | : | Vol. 4, Issue 10 — October 2017 |
| Page No. | : | 157-165 |
| Domain | : | Engineering |
| Type | : | Research Paper |
| ISSN (Online) | : | 2348-4470 |
| ISSN (Print) | : | 2348-6406 |
k-means is one of the simplest unsupervised learning algorithms that solve the well known clusteringproblem. The procedure follows a simple and easy way to classify a given data set through a certain number of clustersfixed apriori. The main idea is to define k centers, one for each cluster. These centers should be placed in a cunning waybecause of different location causes different result. In this research work, Proposed algorithm will perform better whilehandling clusters of circularly distributed data points and slightly overlapped clusters.
T.Mohana Priya, Dr.A.Saradha, “An Optimized repartitioned K-means Cluster algorithm using MapReduce Techniques for Big Data analysis”, International Journal of Advance Engineering and Research Development (IJAERD), Vol. 4, Issue 10, pp. 157-165, October 2017.
