A New Heuristic Reduction Algorithm of Rough Sets Decision-Making Table

Rough set theory acquires rules knowledge through the reduction of the original decision table,and its core part is reduction of attributes.Data after reduction is more valuable and can obtain knowledge more accurately.Presents a new heuristic algorithm,and proposes the detailed steps of the algorithm.And also an example is given to illustrate the algorithm.The algorithm avoids the search for random composition among attributes via using the inconsistency count and the gain of mutual information criteria to value the significance of an attribute,and increases computing speed.From numerical experiments and comparisons,the algorithm provides more precise and simple reduction of attributes than the dynamic reduction algorithm or the standard genetic algorithm does.