Survey Paper | Computer Science & Engineering | India | Volume 4 Issue 1, January 2015
A Survey on Parallel Method for Rough Set using MapReduce Technique for Data Mining
Varda C. Dhande | B.V. Pawar
Abstract: In this paper Present survey on Data mining, Data mining using Rough set Theory and Data Mining using parallel method for rough set Approximation with MapReduce Technique. With the development of Information technology data growing at a tremendous rate, so big data mining and knowledge discovery become a new challenge. Rough set theory has been successfully applied in data mining by using MapReduce programming technique. We use the Hadoop MapReduce System as an Implementation platform. The lower and upper approximations are two basic concept of rough set theory. A parallel method is used for the effective computation of approximation and is improving the performance of data mining. With the benefits of MapReduce it makes our approach more ideal for executing large scale data using parallel method.
Keywords: Data mining, MapReduce, Rough sets, Approximations, Hadoop, HDFS
Edition: Volume 4 Issue 1, January 2015,
Pages: 423 - 426
How to Cite this Article?
Varda C. Dhande, B.V. Pawar, "A Survey on Parallel Method for Rough Set using MapReduce Technique for Data Mining", International Journal of Science and Research (IJSR), https://www.ijsr.net/get_abstract.php?paper_id=SUB15211, Volume 4 Issue 1, January 2015, 423 - 426, #ijsrnet
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