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RHadoop platform for K-Means clustering of big data
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 Title & Authors
RHadoop platform for K-Means clustering of big data
Shin, Ji Eun; Oh, Yoon Sik; Lim, Dong Hoon;
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RHadoop is a collection of R packages that allow users to manage and analyze data with Hadoop. In this paper, we implement K-Means algorithm based on MapReduce framework with RHadoop to make the clustering method applicable to large scale data. The main idea introduces a combiner as a function of our map output to decrease the amount of data needed to be processed by reducers. We showed that our K-Means algorithm using RHadoop with combiner was faster than regular algorithm without combiner as the size of data set increases. We also implemented Elbow method with MapReduce for finding the optimum number of clusters for K-Means clustering on large dataset. Comparison with our MapReduce implementation of Elbow method and classical kmeans() in R with small data showed similar results.
Big data;Hadoop;K-Means clustering;R;RHadoop;
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고차원 자료에서 영향점의 영향을 평가하기 위한 그래픽 방법,안소진;이재은;장대흥;

Journal of the Korean Data and Information Science Society, 2017. vol.28. 6, pp.1291-1300 crossref(new window)
제조 빅데이터 시스템을 위한 효과적인 시각화 기법,류관희;

Journal of the Korean Data and Information Science Society, 2017. vol.28. 6, pp.1301-1311 crossref(new window)
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