Title :
NN classifiers: reducing the computational cost of cross-validation by active pattern selection
Author :
Leisch, Friedrich ; Jain, Lakhmi C. ; Hornik, Kurt
Author_Institution :
Tech. Univ. Wien, Austria
Abstract :
We propose a new approach for leave-one-out cross-validation of neural network classifiers called “cross-validation with active pattern selection” (CV/APS). In CV/APS, the contribution of the training patterns to backpropagation learning is estimated and this information is used for active selection of CV patterns. On two artificial examples, the computational cost of CV can be reduced to 25% of the normal costs with only small or no errors
Keywords :
backpropagation; neural nets; pattern classification; statistical analysis; active pattern selection; backpropagation learning; computational cost reduction; leave-one-out cross-validation; neural network classifiers; training patterns; Artificial neural networks; Australia; Computational efficiency; Cost function; Knowledge engineering; Neural networks; Performance loss; Predictive models; Systems engineering and theory; Testing;
Conference_Titel :
Artificial Neural Networks and Expert Systems, 1995. Proceedings., Second New Zealand International Two-Stream Conference on
Conference_Location :
Dunedin
Print_ISBN :
0-8186-7174-2
DOI :
10.1109/ANNES.1995.499447
