New reduction method based on decision information entropy in decision table
一种新的基于决策熵的决策表约简方法

In decision table, the disadvantages of classical rough reduction algorithm were analyzed. Based on the recent rough entropy of knowledge, the new decision information entropy was proposed with separating consistent objects from inconsistent objects, and the new significance of an attribute was defined. The judgment theorem based on this entropy was obtained with respect to knowledge reduction. Condition attributes were considered to estimate the significance for decision classes, and a heuristic algorithm was proposed. Theoretical analysis shows that the proposed heuristic information was better and more efficient than the others, and experimental results prove the validity of the heuristic algorithm in searching the minimal or optimal reduction.