Dynamic reducts computation analysis based on rough sets

In this paper analysis of reduction and dynamic reducts of an information data is presented. The method of reduction in information system is explained first, the information was assumed to be in a two-dimension or in a matrix form. A discernibility matrix of the data was constructed, and then all reducts from that matrix were found. The best (optimum) reduct was selected from all reducts; that was achieved by considering the one with the highest level of frequency by using Java programming and Weka tool. Three methods of dynamic reducts computation are introduced namely: The new type of Reduct in the object-oriented rough set model which is called dynamic reduct, the method of dynamic reduct calculation based on calculating of reduct traces and the generation F-dynamic reduct using cascading Hashes. The analysis of those three methods led to their improvement through adding one step in each algorithm which was the method of getting the optimum reducts from all reducts calculated in first steps of each algorithm. As result, the dynamic reducts were generated from optimum reducts and not from all reducts. Thus by generating an improved dynamic reducts, improvement of those three methods for calculation of dynamic reducts is achieved.