DocumentCode
3031690
Title
Analysis of sampling methods in the learning process of ensemble neural networks
Author
Lopez, Miguel ; Melin, Patricia
Author_Institution
Univ. Autonoma de Baja California, Tijuana
fYear
2007
fDate
24-27 June 2007
Firstpage
604
Lastpage
609
Abstract
When developing learning algorithms for ensemble neural networks it is of fundamental importance to use a sampling method. In this paper a comparative analysis is made, between a sampling data method based on the mean square error for the training of ensemble neural networks and cross validation sampling method.
Keywords
learning (artificial intelligence); mean square error methods; neural nets; sampling methods; comparative analysis; cross validation sampling method; ensemble neural networks; learning; mean square error; sampling data method; Algorithm design and analysis; Artificial neural networks; Biological neural networks; Humans; Mean square error methods; Neural networks; Neurons; Sampling methods; Testing; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Information Processing Society, 2007. NAFIPS '07. Annual Meeting of the North American
Conference_Location
San Diego, CA
Print_ISBN
1-4244-1213-7
Electronic_ISBN
1-4244-1214-5
Type
conf
DOI
10.1109/NAFIPS.2007.383909
Filename
4271132
Link To Document