Title :
The Inverse Problem of Support Vector Machines Solved by a New Intelligence Algorithm
Author :
Wang, Jingmin ; Ren, Guoqiao
Author_Institution :
Dept. of Economy & Manage., North China Electr. Power Univ., Baoding
Abstract :
An inverse problem of support vector machines (SVMs) was investigated. The inverse problem is how to split a given dataset into two clusters such that the margin between the two clusters attains the maximum. Here the margin is defined according to the separating hyper plane generated by support vectors. It is difficult to give an exact solution to this problem. An immunogenetic particle swarm incorporated intelligence algorithm was proposed to solve this problem. This study on the inverse problem of SVMs is motivated by designing a heuristic algorithm for generating decision trees with high generalization capability. The application in the recognition of the bank risk shows it is effective
Keywords :
decision trees; generalisation (artificial intelligence); genetic algorithms; particle swarm optimisation; support vector machines; decision trees; generalization capability; genetic algorithm; heuristic algorithm; immunogenetic particle swarm; intelligence algorithm; inverse problem; support vector machines; Clustering algorithms; Decision trees; Entropy; Inverse problems; Kernel; Machine intelligence; Machine learning; Particle swarm optimization; Support vector machine classification; Support vector machines; genetic algorithm; incorporated intelligence algorithm; inverse problem; penalty factor; support vector machine;
Conference_Titel :
Cognitive Informatics, 2006. ICCI 2006. 5th IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
1-4244-0475-4
DOI :
10.1109/COGINF.2006.365571
