Obtaining Approximation with Data Cube using Map-Reduce

Abstract

Data mining is a field that has an important contribution to data analysis, discovery of new meaningful knowledge, and autonomous decision making. Whereas, the rough set theory offers a viable approach for decision rule extraction from data. With the data cube we tried to put data in multidimensional way and accessed that data via map reduce. The adequate quantity or supply of data, coupled with the need for powerful data analysis tools, i.e. where data is rich but information is in poor situation. The proposed algorithm is been compared with other different rough set approximation approaches. Our algorithm to achieve approximation for decision rules has better performance. This proposed algorithm has been more efficient to obtain approximation.
DOI: 10.17762/ijritcc2321-8169.1507107