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Paper Details
Paper Title
Rough Approximation Methods: Inter-Table and Data Cube
Authors
  Prachi Patil,  Anilkumar Kadam,  Rohitkumar Kawhale
Abstract
Data mining as an important contribution to data analysis, data discovery and autonomous decision making. Rough set theory (RST) is the technique in data mining is an approach for decision rule extraction from data. Lower approximation, Upper approximation and boundary region are the principle parts of RST. There are two different methods to obtain rough approximation based on data cube and inter-table comparison. In data cube method, data has put in multidimensional way and accessed via map reduce. Another technique also based on map reduce, but it divides the given dataset into number of sub tables. In this paper, we are going to analyze these two different method of computing rough approximation.
Keywords- Rough Set, Lower approximation, Upper Approximation, Data Cube
Publication Details
Unique Identification Number - IJEDR1504001Page Number(s) - 1-4Pubished in - Volume 3 | Issue 4 | October 2015DOI (Digital Object Identifier) -    Publisher - IJEDR (ISSN - 2321-9939)
Cite this Article
  Prachi Patil,  Anilkumar Kadam,  Rohitkumar Kawhale,   "Rough Approximation Methods: Inter-Table and Data Cube", International Journal of Engineering Development and Research (IJEDR), ISSN:2321-9939, Volume.3, Issue 4, pp.1-4, October 2015, Available at :http://www.ijedr.org/papers/IJEDR1504001.pdf
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