Adaptive Higher Order Neural Networks for Effective Data Mining View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2009

AUTHORS

Shuxiang Xu , Ling Chen

ABSTRACT

A new adaptive Higher Order Neural Network (HONN) is introduced and applied in data mining tasks such as determining automobile yearly losses and edible mushrooms. Experiments demonstrate that the new adaptive HONN model offers advantages over conventional Artificial Neural Network (ANN) models such as higher generalization capability and the ability in handling missing values in a dataset. A new approach for determining the best number of hidden neurons is also proposed. More... »

PAGES

165-173

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-3-642-01216-7_18

DOI

http://dx.doi.org/10.1007/978-3-642-01216-7_18

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1049732107


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