DocumentCode
1905628
Title
An efficient algorithm for the binary classification of patterns using MLP-networks
Author
Fanelli, S. ; Martino, M. Di ; Protasi, M.
Author_Institution
Dipartimento di Matematica, Roma Univ., Italy
fYear
1993
fDate
1993
Firstpage
936
Abstract
An alternative to the back propagation algorithm for the effective training of multi-layer perceptron (MLP)-networks with binary output is described. The algorithm determines the optimal set of weights by an iterative scheme based on the singular value decomposition (SVD) method and the Fletcher and Reeves version of the conjugate gradient method
Keywords
feedforward neural nets; iterative methods; learning (artificial intelligence); pattern recognition; MLP-networks; binary classification; binary output; conjugate gradient method; iterative scheme; multi-layer perceptron; pattern classification; singular value decomposition; Computer networks; Gradient methods; Iterative algorithms; Iterative methods; Matrix decomposition; Neural networks; Neurons; Nonlinear equations; Pattern recognition; Singular value decomposition;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks, 1993., IEEE International Conference on
Conference_Location
San Francisco, CA
Print_ISBN
0-7803-0999-5
Type
conf
DOI
10.1109/ICNN.1993.298683
Filename
298683
Link To Document