Rough Set Methods for Large and Spare Data in EAV Format

Abstract

In this article we discuss a computationally effective method for computing approximate decision reducts of large data sets. We consider the EAV (entity-attribute-value) which efficiently stores sparse data sets and we propose new implementations of Maximum Discernibility heuristic for data sets represented in this format.