Detail Support Vector Cluster Labeling Using MapReduce   Oleh:  Han, Sangwoo ; Lee, Sujee ; Lee, Jaewook Jenis: Article from Proceeding Dalam koleksi: The 14th Asia Pacific Industrial Engineering and Management Systems Conference (APIEMS), 3-6 December 2013 Cebu, Philippines, page 1-5. Topik: Support Vector Clustering; Cluster Labeling; MapReduce Fulltext: 1114.pdf (2.37MB) Isi artikel We are at the beginning of the big data era. Hadoop, an open-source implementation of Google’s distributed file system provides an easily applicable mechanism for many different problems with the aid of the MapReduce framework for distributed data processing. In this paper, we introduce a way to implement Hadoop distributive system in R, which makes it more accessible for broad range of applications. We adapt map-reduce paradigm to demonstrate this parallel speed-up technique. We use the Support Vector Clustering (SVC) method for the clustering algorithm and dynamical system based labeling method. In these algorithms, especially in the step for solving the dynamical system, the computational cost is very high. Our experiment shows time reduction in Support Vector Clustering time by adopting parallelized processing of dynamical systems. Opini Anda Klik untuk menuliskan opini Anda tentang koleksi ini! Kembali

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