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Adaptive Higher Order Neural networks for Effective data Mining
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.
History
Publication title
Sixth International Symposium on Neural Networks (ISNN 2009)Editors
J KacprzykPagination
165-173ISBN
978-3-642-01216-7Department/School
School of Information and Communication TechnologyPublisher
Springer-VerlagPlace of publication
Berlin, HeidelbergEvent title
International Symposium on Neural Networks (ISNN)Event Venue
Wuhan, ChinaDate of Event (Start Date)
2009-05-26Date of Event (End Date)
2009-05-29Rights statement
The original publication is available at www.springerlink.comRepository Status
- Restricted