The Realization of the Sample Learning Based on Differential Evolution Algorithm

Article Preview

Abstract:

Differential evolution algorithm is a kind of heuristic random search algorithm, and the traditional sample learning is to find a inductive assertion including all positive examples but not all counter-examples in the example space. But this process is endless and cumbersome because of the large number of the samples. The merit of difference evolution algorithm is searching in the community. So this paper using this merit to combine with sample learning then promoting efficiency.

You might also be interested in these eBooks

Info:

Periodical:

Advanced Materials Research (Volumes 616-618)

Pages:

2239-2243

Citation:

Online since:

December 2012

Export:

Price:

Permissions CCC:

Permissions PLS:

Сopyright:

© 2013 Trans Tech Publications Ltd. All Rights Reserved

Share:

Citation:

[1] J.Quinlan, in: Induction of Decision Tree, Machine Learning, I: 1(1986)

Google Scholar

[2] Dietterich T G,Lathrop R H,Lozano P T, in:Solving the multiple—instance problem with axisparallel rectangles[J], Artificial Intelligence, 1997, 89(1—2): 31—71.

DOI: 10.1016/s0004-3702(96)00034-3

Google Scholar

[3] L.O Valiaat,in: Learning Disjunction of Conjunction, Proc IJCAI'85, Los Angeles,CA (1985)

Google Scholar

[4] Vesterstrom J, ThomsenR, in:A Comparative Study of DifferentialEvolution Particle Swarm Optimization and Evolutionary Algorithms on NumericalBenchmark Problems[A], In Proceedings of the IEEE Congress on Evolutionary Computation, Piscataway, IEEE, 2004: 1980-1987

DOI: 10.1109/cec.2004.1331139

Google Scholar

[5] StornR, PriceK, in: Differential Evolution-A Simple and Efficient Heuristic for Global Optimization over Continuous Space[J], Journal of Global Optimization, 1997, 11: 341-359.

Google Scholar