DocumentCode
1264458
Title
Neural network classification: a Bayesian interpretation
Author
Wan, Eric A.
Author_Institution
Dept. of Electr. Eng., Stanford Univ., CA, USA
Volume
1
Issue
4
fYear
1990
fDate
12/1/1990 12:00:00 AM
Firstpage
303
Lastpage
305
Abstract
The relationship between minimizing a mean squared error and finding the optimal Bayesian classifier is reviewed. This provides a theoretical interpretation for the process by which neural networks are used in classification. A number of confidence measures are proposed to evaluate the performance of the neural network classifier within a statistical framework
Keywords
Bayes methods; error statistics; minimisation; neural nets; Bayesian classifier; Bayesian interpretation; mean squared error; neural network classifier; statistical framework; Bayesian methods; Circuits; Contracts; Hopfield neural networks; Least squares approximation; Network address translation; Neural networks; Probability; Random variables; Space technology;
fLanguage
English
Journal_Title
Neural Networks, IEEE Transactions on
Publisher
ieee
ISSN
1045-9227
Type
jour
DOI
10.1109/72.80269
Filename
80269
Link To Document