paper to be published by AI journal and its code

[Zhi-Hua Zhou]

Dear Colleagues,

Below is a paper accepted by AI Journal:

Zhi-Hua Zhou, Jianxin Wu, Wei Tang. Ensembling neural networks: many could
be better than all.

Abstract: Neural network ensemble is a learning paradigm where many neural
networks are jointly used to solve a problem. In this paper, the
relationship between the ensemble and its component neural networks is
analyzed from the context of both regression and classification, which
reveals that it may be better to ensemble many instead of all of the neural
networks at hand. This result is interesting because at present, most
approaches ensemble all the available neural networks for prediction. Then,
in order to show that the appropriate neural networks for composing an
ensemble can be effectively selected from a set of available neural
networks, an approach named GASEN is presented. GASEN trains a number of
neural networks at first. Then it assigns random weights to those networks
and employs genetic algorithm to evolve the weights so that they can
characterize to some extent the fitness of the neural networks in
constituting an ensemble. Finally it selects some neural networks based on
the evolved weights to make up the ensemble. A large empirical study shows
that, comparing with some popular ensemble approaches such as Bagging and
Boosting, GASEN can generate neural network ensembles with far smaller sizes
but stronger generalization ability. Furthermore, in order to understand the
working mechanism of GASEN, the bias-variance decomposition of the error is
provided in this paper, which shows that the success of GASEN may lie in
that it can significantly reduce the bias as well as the variance.

The pdf version of this paper is now available at
http://cs.nju.edu.cn/people/zhouzh/zhouzh.files/Publication/aij02.pdf

The matlab code of GASEN now is available at
http://cs.nju.edu.cn/people/zhouzh/zhouzh.files/MLNN_Group/freeware/Gasen.zip

Enjoy it!

Best Regards
Zhihua
-----------------------------------------------
Zhi-Hua ZHOU        Ph.d.

National Lab for Novel Software Technology
Nanjing University
Hankou Road 22
Nanjing 210093, P.R.China

Tel: +86-25-359-3163      Fax: +86-25-330-0710
URL: http://cs.nju.edu.cn/people/zhouzh/
Email: zhouzh at nju.edu.cn
-----------------------------------------------