A constructive algorithm for training heterogeneous neural network ensemble

Authors:
Xianghua Fu;Zhiqiang Wang;Boqin Feng
Affiliations:
College of Information Engineering, Shenzhen University, Shenzhen, China;College of Information Engineering, Shenzhen University, Shenzhen, China;School of Electronics and Information Engineering, Xi'an Jiaotong University, Xi'an, China
Venue:
RSKT'06 Proceedings of the First international conference on Rough Sets and Knowledge Technology
Year:
2006

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Abstract

This paper presents a new algorithm to construct a neural network ensemble (NNE) based on heterogeneous component neural networks with negative correlation learning. The constructive algorithm consists of two parts: a sub-algorithm to construct best heterogeneous component neural networks with negative correlation learning dynamically (CBHNN), and a sub-algorithm to construct heterogeneous NNE with trained heterogeneous neural networks incrementally (CHNNE). The experiment results showe that HNNE is better than the traditional homological NNE method