Description: GASEN is a selective ensemble method using genetic algorithm to help select a subset of neural networks (or other learners, with appropriate modification) to compose an ensemble, which is better than directly ensembling all the neural networks available.
Reference: Z.-H. Zhou, J. Wu, and W. Tang. Ensembling neural networks: Many could be better than all. Artificial Intelligence, 2002, vol.137, no.1-2, pp.239-263.
ATTN: This package is free for academic usage. You can run it at your own risk. For other purposes, please contact Prof. Zhi-Hua Zhou (zhouzh@nju.edu.cn).
Requirement: To use this package, the GAOT toolbox must be available. Refer: C.R. Houck, J.A. Joines, and M.G. Kay. A genetic algorithm for function optimization: a Matlab implementation. Technical Report: NCSU-IE-TR-95-09, North Carolina State University, Raleigh, NC, 1995.
Data format: Refer the readme file in the package.
ATTN2: This package was developed by Mr. Wei Tang (tangwei@ai.nju.edu.cn). For any problem concerning the code, please feel free to contact Mr. Tang.
Download:
code (5.1Kb)