Parallel attribute reduction based on mapreduce

Abstract

With the explosive increment of data, varieties of the parallel attribute reduction algorithm have been studied. To promote its efficiency, this paper proposes a new parallel attribute reduction algorithm based on MapReduce. It contains three parts, parallel computation of a simplified decision table, parallel computation of attribute significance and parallel computation of decision table. Data with different sizes are experimented. The experimental result shows that our algorithm has the ability of processing massive data with efficiency.