Title : 
Off-line structural risk minimization and BARTMAP-S
         
        
            Author : 
Verzi, Stephen J. ; Heileman, Gregory L. ; Georgiopoulos, Michael ; Anagnostopoulos, Georgios
         
        
            Author_Institution : 
Dept. of Comput. Sci., New Mexico Univ., Albuquerque, NM, USA
         
        
        
        
            fDate : 
6/24/1905 12:00:00 AM
         
        
        
        
            Abstract : 
BARTMAP-S (Simplified Boosted ARTMAP) is a neural network architecture with which structural risk minimization can be performed, although indirectly. BARTMAP-S is trained in an online fashion, consistent with the original way intended for the fuzzy ARTMAP neural network architecture. We propose an extension to BARTMAP-S for conducting off-line learning. Consequently, this alternate mode of learning will allow us to conduct structural risk minimization more directly. We describe the new architecture and present some empirical results to demonstrate the usefulness of structural risk minimization in learning with an ARTMAP-based neural network
         
        
            Keywords : 
ART neural nets; generalisation (artificial intelligence); learning (artificial intelligence); neural net architecture; BARTMAP-S; Simplified Boosted ARTMAP; adaptive resonance theory; empirical risk minimization; generalization performance; neural network architecture; off-line learning; off-line structural risk minimization; overlapping pattern classes; Adaptive systems; Computer networks; Computer science; Fuzzy logic; Machine learning; Neural networks; Resonance; Risk management; Virtual colonoscopy;
         
        
        
        
            Conference_Titel : 
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
         
        
            Conference_Location : 
Honolulu, HI
         
        
        
            Print_ISBN : 
0-7803-7278-6
         
        
        
            DOI : 
10.1109/IJCNN.2002.1007542