An Efficient Parallel Fuzzy Rough set Based Rule Generation Using Map Reduce

Abstract: Massive background knowledge detection shows a challenge with the information capacity growing at an unprecented speed. MapReduce has succeeded large computation. The latterly introduced MapReduce method has more consideration from industry for its wide ranging analysis. Rough set concept is a plow which is used to obtain information from completeness data. The proposed system using unrefined sets based knowledge discovery from big data, the parallel approximate set methods for information discovery. The propose fuzzy supported pattern generation. Compare with existing algorithm the proposed system give high accuracy of rule generation based fuzzy based rough set.

Keywords: MapReduce; Bigdata; Roughset theory; fuzzy based rule generation.