A Parallel Clustering Method Study Based on MapReduce

Clustering is considered as the most important task in data mining. The goal of clustering is to determine the intrinsic grouping in a set of unlabeled data. Many practical application problems should be solved with clustering method. It has been widely applied into all kinds of areas, such marketing, biology, library, insurance, earth-quake study, and World Wide Web (WWW) and so on. Many clustering methods have been studied, such as k-means, Fisher clustering, and Koehon clustering and so on.

Provided by: Indiana University Topic: Big Data Date Added: Jun 2012 Format: PDF

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