Research on rules reduction for real value attribute information system based on fuzzy similarity

To overcome the shortcomings of information loss and reduction mistakes in traditional method of rules reduction, a new algorithm of rules reduction for real value attribute information system was proposed. Fuzzy sets’ similarity was introduced into rules reduction of information system based on rough sets theory. The corresponding condition attribute value of every rule was from 0 to 1 by evaluating every real attribute value as unitary one. Every rule was considered as a fuzzy set to denote rules similarity by fuzzy sets similarity. The rules reduction was accomplished by the improved similarity coefficient of fuzzy sets during the reduction process, and the algorithm was tested by international rice information system (IRIS) database. The experimental results show that the algorithm can correctly reduce rules reduction for real value attribute information system.