Method and Software for Extracting Fuzzy Classification Subtractive Clustering
Stephen L. Chiu · 1996
We present a fast and robust method for extracting fuzzy classification rules from data. The method uses subtractive clustering to obtain the initial rules; the rule parameters are then optimized by using an efficient gradient descent algorithm. We also describe a user-friendly Macintosh software, called RIFLEX, in which this rule extraction method has been implemented.