Title :
Adaptive Higher Order Neural Networks
Author :
Xu, Shuxiang ; Chen, Ling
Author_Institution :
Sch. of Comput. & IS, Univ. of Tasmania, Launceston, TAS, Australia
Abstract :
This paper introduces an adaptive higher order neural network (HONN) and applies it in data mining such as Australian credit card assessment. The proposed adaptive HONN model offers significant advantages over conventional artificial neural network (ANN) models such as more accurate predictions and the ability in handling incomplete/missing values in a dataset. A new approach for determining the best number of hidden neurons is also proposed.
Keywords :
data mining; neural nets; ANN; HONN; adaptive higher order neural network; data mining; Artificial neural networks; Australia; Backpropagation algorithms; Computer networks; Data analysis; Data mining; Intelligent systems; Neural networks; Neurons; Predictive models; Data Mining; Higher Order Neural Networks;
Conference_Titel :
Intelligent Systems, 2009. GCIS '09. WRI Global Congress on
Conference_Location :
Xiamen
Print_ISBN :
978-0-7695-3571-5
DOI :
10.1109/GCIS.2009.296
