An Efficient Algorithm for Clustering Data Using Map-Reduce Approach?

We have been studying the problem of clustering data objects. As we have implemented a new algorithm EMaRC which is An Efficient Map Reduce algorithm for Clustering Data. In clusters Feature selection is the most important part of the clustering process that involves and identifying the set of features of a subset, at which they produces accurate and accordant results with the original set of features. The main concept behind this paper is that, to give the effective outcomes of clustering features. In this the nature of clustering and some more concepts serves for processing large data sets. A map-reduce concept is involved followed by feature selection algorithm which affects the entire process of clustering to get the most effective and features produces efficiently. While efficiency concerns, the time complexity is desirable component, which the time required to find effective features, where effectiveness is related to the quality of the features of subsets. Based on these criteria, a cluster based map-reduce feature selection approach, is proposed and evaluated in this paper.