DocumentCode
315240
Title
The generalization capabilities of ARTMAP
Author
Heileman, Gregory L. ; Georgiopoulos, Michael ; Healy, MIichael J. ; Verzi, Stephen J.
Author_Institution
Dept. of Electr. & Comput. Eng., New Mexico Univ., Albuquerque, NM, USA
Volume
2
fYear
1997
fDate
9-12 Jun 1997
Firstpage
1068
Abstract
Bounds on the number of training examples needed to guarantee a certain level of generalization performance in the ARTMAP architecture are derived. Conditions are derived under which ARTMAP can achieve a specific level of performance assuming any unknown, but fixed, probability distribution on the training data
Keywords
ART neural nets; generalisation (artificial intelligence); learning (artificial intelligence); neural net architecture; performance evaluation; probability; ART neural nets; ARTMAP; PAC learning; generalization; learning algorithm; neural architecture; probability distribution; Computer architecture; Computer science; Learning systems; Machine learning; Neural networks; Probability distribution; Target tracking; Testing; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks,1997., International Conference on
Conference_Location
Houston, TX
Print_ISBN
0-7803-4122-8
Type
conf
DOI
10.1109/ICNN.1997.616176
Filename
616176
Link To Document