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 ...

• Type: Conference
• Year: 2007
• Where: GECCO
• Authors: Rui Li, Bir Bhanu, Krzysztof Krawiec
• Keywords: Coevolutionary Computational Classification, GECCO 2007, Pattern Recognition, Support Vector Machines