An Optimized repartitioned K-means Cluster algorithm using MapReduce Techniques for Big Data analysis-IJAERD

k-means is one of the simplest unsupervised learning algorithms that solve the well known clustering problem. The procedure follows a simple and easy way to classify a given data set through a certain number of clusters fixed apriori. The main idea is to define k centers, one for each cluster. These centers should be placed in a cunning way because of different location causes different result. In this research work, Proposed algorithm will perform better while handling clusters of circularly distributed data points and slightly overlapped clusters.