Title :
Probabilistic simplified fuzzy ARTMAP (PSFAM) [and application to biosignal data]
Author :
Jervis, B.W. ; Garcia, T. ; Giahnakis, E.P.
fDate :
7/1/1999 12:00:00 AM
Abstract :
The probabilistic simplified fuzzy ARTMAP (PSFAM) has been developed for fast training and offline or online learning and classification of data together with a probability measure of confidence in the classification. A simplified fuzzy ARTMAP (SFAM) and a Bayes classifier are combined. Using a committee of SFAMs and brain-evoked response data from four groups of subjects, classification accuracies in the range 87-97% are achieved together with ideal or near-ideal medical statistics. The limitations appeared to be associated with the data
Keywords :
ART neural nets; belief networks; fuzzy neural nets; inference mechanisms; learning (artificial intelligence); medical expert systems; pattern classification; Bayes classifier; biosignal data; brain-evoked response data; classification of data; fast training; ideal medical statistics; offline learning; online learning; prediction errors; probabilistic simplified fuzzy ARTMAP; probability measure of confidence;
Journal_Title :
Science, Measurement and Technology, IEE Proceedings -
DOI :
10.1049/ip-smt:19990383
