The generalization capabilities of ARTMAP

IEEE International Conference on Neural Networks - Conference Proceedings

Volumn 2, Issue , 1997, Pages 1068-1071

  Heileman, G L ^a   Georgiopoulos, M ^b   Healy, M J ^c   Verzi, S J ^a  

^a University of New Mexico   (United States)

^b University of Central Florida   (United States)

^c BOEING COMPANY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

GENERALIZATION CAPABILITY; GENERALIZATION PERFORMANCE; TRAINING DATA; TRAINING EXAMPLE;

PROBABILITY DISTRIBUTIONS; LEARNING SYSTEMS; PROBABILITY; PROBLEM SOLVING;

NEURAL NETWORKS;

GENERALIZATION CAPABILITY;

EID: 0030650654     PISSN: 10987576     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICNN.1997.616176     Document Type: Conference Paper

References (4)

1. A. Blumer, A. Ehrenfeucht, D. Haussler, and M. K. Warmuth. Learnability and the Vapnik-Chervonenkis dimension. Journal ofthe ACM, 36(4):929-965, 1989.
2. G. A. Carpenter, S. Grossberg, and J. H. Reynolds. ARTMAP: Supervised real-time learning and classification of nonstationary data by a self-organizing neural network. Neural Networks, 4(5):565-588,1991.
3. M. Georgiopoulos, J. Huang, and G. L. Heileman. Properties of learning in ARTMAP. Neural Networks, 7(3):495-506, 1994.
4. L. G. Valiant. A theory of the learnable. Communications of the ACM, 27(11): 1134-1142, 1984.