DocumentCode
290295
Title
An invariance property of neural networks
Author
Gish, Herbert ; Siu, Manhung
Author_Institution
BBN Syst. & Technol. Corp., Cambridge, MA, USA
Volume
ii
fYear
1994
fDate
19-22 Apr 1994
Abstract
It is often the case that one wants to apply a neural network classifier, trained with a particular mix of the training classes, to a situation where the classes occur in a different proportion. The originally trained network will not be appropriate for the new situation. The authors show that only a single weight of the network needs to be modified to accommodate the network to the new situation. The other weights are invariant to the change in mix
Keywords
invariance; learning (artificial intelligence); neural nets; pattern classification; classifier; invariance property; neural networks; training classes; weights; Equations; Neural networks; Testing;
fLanguage
English
Publisher
ieee
Conference_Titel
Acoustics, Speech, and Signal Processing, 1994. ICASSP-94., 1994 IEEE International Conference on
Conference_Location
Adelaide, SA
ISSN
1520-6149
Print_ISBN
0-7803-1775-0
Type
conf
DOI
10.1109/ICASSP.1994.389599
Filename
389599
Link To Document