DocumentCode :
3252796
Title :
Training set-based performance measures for neural net hypothesis testing
Author :
Levine, Robert Y. ; Khuon, Timothy S.
Author_Institution :
MIT Lincoln Lab., Lexington, MA, USA
Volume :
4
fYear :
1992
fDate :
7-11 Jun 1992
Firstpage :
252
Abstract :
Performance measures for neural network hypothesis testing are derived based on the statistics of the training set. The training set-based measures are contrasted with maximum a posteriori probability (MAP) test measures. It is shown that the training set-based and MAP test probabilities are equal if the training set is proportioned according to the prior probabilities of the hypotheses. Applications of training set-based measures are suggested for neural net and training set design
Keywords :
adaptive systems; learning by example; neural nets; probability; maximum a posteriori probability; neural net hypothesis testing; performance measures; training set design; training set-based measures; Adaptive systems; Distributed computing; Gaussian noise; Laboratories; Maximum a posteriori estimation; Neural networks; Neurons; Probability; Statistical analysis; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
Type :
conf
DOI :
10.1109/IJCNN.1992.227333
Filename :
227333
Link To Document :
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