Active Learning Based on New Localized Generalization Error Model for Training RBFNN

San Feng Chen; Wei Liu; Xian Yi Ren; Hui Jing Wang

doi:10.4028/www.scientific.net/AMR.108-111.1381

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HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 108-111Active Learning Based on New Localized...

Active Learning Based on New Localized Generalization Error Model for Training RBFNN

Abstract:

A new active learning based on a new localized generalization error model is proposed in the paper for training RBFNN. The samples with largest local generalization error are selected and labelled. The experimental results show that the proposed algorithm is effective, which can select the most informative samples and fewer samples are necessary.

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Periodical:

Advanced Materials Research (Volumes 108-111)

Pages:

1381-1385

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.108-111.1381

Citation:

Cite this paper

Online since:

May 2010

Authors:

San Feng Chen, Wei Liu, Xian Yi Ren, Hui Jing Wang

Keywords:

Active Learning, Localized Generalization Error, RBFNN

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