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GECCO
2007
Springer

Hybrid coevolutionary algorithms vs. SVM algorithms

9 years 6 months ago
Hybrid coevolutionary algorithms vs. SVM algorithms
As a learning method support vector machine is regarded as one of the best classifiers with a strong mathematical foundation. On the other hand, evolutionary computational technique is characterized as a soft computing learning method with its roots in the theory of evolution. During the past decade, SVM has been commonly used as a classifier for various applications. The evolutionary computation has also attracted a lot of attention in pattern recognition and has shown significant performance improvement on a variety of applications. However, there has been no comparison of the two methods. In this paper, first we propose an improvement of a coevolutionary computational classification algorithm, called Improved Coevolutionary Feature Synthesized EM (I-CFS-EM) algorithm. It is a hybrid of coevolutionary genetic programming and EM algorithm applied on partially labeled data. It requires less labeled data and it makes the test in a lower dimension, which speeds up the testing. Then, we ...
Rui Li, Bir Bhanu, Krzysztof Krawiec
Added 07 Jun 2010
Updated 07 Jun 2010
Type Conference
Year 2007
Where GECCO
Authors Rui Li, Bir Bhanu, Krzysztof Krawiec
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