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Classifier ensemble selection using hybrid genetic algorithms
- Source :
- Pattern Recognition Letters. 29:796-802
- Publication Year :
- 2008
- Publisher :
- Elsevier BV, 2008.
-
Abstract
- This paper proposes a hybrid genetic algorithm for classifier ensemble selection. In this paper, two local search operations used to improve offspring prior to replacement are proposed. The operations are parameterized in order to control the computation time. Experimental results and statistical tests demonstrate the effectiveness of the proposed hybrid genetic algorithm and related local search operations.
- Subjects :
- Ensemble selection
Hybrid genetic algorithms
business.industry
Computation
Parameterized complexity
Machine learning
computer.software_genre
Signal classification
Artificial Intelligence
Signal Processing
Computer Vision and Pattern Recognition
Artificial intelligence
business
computer
Classifier (UML)
Software
Mathematics
Statistical hypothesis testing
Subjects
Details
- ISSN :
- 01678655
- Volume :
- 29
- Database :
- OpenAIRE
- Journal :
- Pattern Recognition Letters
- Accession number :
- edsair.doi...........fbf06b2d3016e665fb2d9f0bbfb0cb93