This document provides an overview and comparative analysis of the K-Means++ and Mini Batch K-Means clustering algorithms in cloud computing using MapReduce. It first introduces cloud computing and its advantages for processing big data using Hadoop MapReduce. It then discusses the K-Means++ algorithm as an improved version of the standard K-Means algorithm that initializes cluster centroids more intelligently. Finally, it compares the performance of K-Means++ and Mini Batch K-Means when implemented using MapReduce for large-scale clustering in cloud environments.
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IRJET- Comparatively Analysis on K-Means++ and Mini Batch K-Means Clustering Algorithm in Cloud Computing with Map Reduce