DocumentCode
1905575
Title
On the speed of training networks with correlated features
Author
Bakker, Robert R N ; Kraaijveld, Martin A. ; Duin, Robert P W ; Schmidt, Wouter F.
Author_Institution
Dept. of Appl. Phys., Delft Univ. of Technol., Netherlands
fYear
1993
fDate
1993
Firstpage
919
Abstract
The learning speed of the adaptive linear combiner is determined by the condition number of the input correlation matrix of the training data. With known properties of such correlation matrices, it is shown that increasing the dimensionality of the feature space of an adaptive linear combiner will never increase its learning speed. In fact, the learning speed will at best remain equal, but will deteriorate in most cases
Keywords
learning (artificial intelligence); neural nets; adaptive linear combiner; condition number; correlated features; dimensionality; feature space; input correlation matrix; learning speed; training networks; Adaptive signal processing; Automatic logic units; Eigenvalues and eigenfunctions; Learning systems; Least squares approximation; Pattern recognition; Physics; Time factors; Training data; Vectors;
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.1993.298680
Filename
298680
Link To Document