Selective Ensemble Based on Moore-Penrose Pseudo-inverse

YANG Xiao-shuang; WANG Yuan-yuan

doi:10.3969/j.issn.1003-501x.2009.11.028

[1] Dietterich T. Machine learning research:four current directions [J]. AI Magazine(S0738-4602),1997,18(4):97-136.

[2] Efron B,Tibshirani R. An Introduction to the Bootstrap [M]. New York :Chapman & Hall,1993.

[3] Freund Y. Boosting a weak algorithm by majority [J]. Information and Computation(S0890-5401),1995,121(2):256-285.

[4] Zhou Z,Wu J,Tang W. Ensembling neural networks: many could be better than all [J]. Artificial Intelligence(S0004-3702),2002,137:239-263.

[5] Krogh A,Vedelsby J. Neural network ensembles,cross validation,and active learning [M]// Tesauro G. Advances in Neural Information Processing Systems,Cambridge,MA,USA:MIT Press,1995,7:231-238.

[6] AN kai,SONG Ni-ding,MA Jia-guang. Generalized inverse matrix method for sliding mode variable structure control of satellite attitude [J]. Opto-Electronic Engineering,2007,34(5):1-4.

[8] Blake C,Keogh E,Merz C. UCI Repository of machine learning databases [EB/OL]. (2008-8-15). http://www.ics.uci.edu/~mlearn/MLRepository.html.

[10] Houck C,Joines J,Kay M. A genetic algorithm for function optimization: A Matlab implementation,Tech Rep: NCSU-IE-TR-95-09 [R]. 1995.

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