Title :
Training of a fuzzy classifier with polyhedral regions
Author :
Takigawa, Tomoo ; Spimozaki, T. ; Abe, Shigeo
Author_Institution :
Graduate Sch. of Sci. & Technol., Kobe Univ., Japan
Abstract :
We discuss a fuzzy classifier with polyhedral regions. First, we generate an initial convex hull with the maximum dimension using the data, included in a class, in the general positions. Next, we modify the convex hull using one training datum at a time by the dynamic convex hull generation method. Finally, for each convex hull we define a membership function using the minimum operator and tune the slopes of the membership functions using the training data. We demonstrate the effectiveness of our method using two benchmark data sets
Keywords :
fuzzy set theory; learning (artificial intelligence); pattern classification; dynamic convex hull generation method; fuzzy classifier; membership function; membership functions; minimum operator; polyhedral regions; training data; Data mining; Ellipsoids; Iris; Lyapunov method; Multi-layer neural network; Neural networks; Training data; Vectors;
Conference_Titel :
Neural Networks, 2001. Proceedings. IJCNN '01. International Joint Conference on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-7044-9
DOI :
10.1109/IJCNN.2001.939558