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 Kacprzyk
Pagination
165-173
ISBN
978-3-642-01216-7
Department/School
School of Information and Communication Technology
Publisher
Springer-Verlag
Place of publication
Berlin, Heidelberg
Event title
International Symposium on Neural Networks (ISNN)
Event Venue
Wuhan, China
Date of Event (Start Date)
2009-05-26
Date of Event (End Date)
2009-05-29
Rights statement
The original publication is available at www.springerlink.com
Repository Status
Restricted
Socio-economic Objectives
Information systems, technologies and services not elsewhere classified