Main Approaches

This section analyses and describes the implementation details and practical issues of Big Data analysis techniques. The focus is on algorithms for associated rule mining and cluster analysis. The last part discusses a technique for distributed and parallel analysis of large data sets. The Subsection IV-A2 discusses the Apriori algorithm, Subsection IV-A3 discusses the Frequent Pattern (FP)-Growth algorithm and Subsection IV-B1 discusses the K-means and K-means++ algorithm. Finally Subsection IV-C discusses the MapReduce framework.

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