Scalable Quick Reduct Algorithm
Praveen Kumar Singh, P. S. V. S. Sai Prasad · 2016
Feature selection by reduct computation is the key technique for knowledge acquistion using rough set theory. Existing MapReduce based reduct algorithms use Hadoop Map Reduce framework, which is not suitable for iterative algorithms. Paper aims to design and implementation of Iterative MapReduce based Quick reduct algorithm using Twister framework. The proposed In_MRQRA Algorithm has partial granular level computations at mappers and granular computations at reducer. Experimental analysis on KDD-Cup99 dataset empirically established the relevence of proposed approach.