SVM Multi-Classification Optimization Research based on Multi-Chromosome Genetic Algorithm

摘要

Regarding SVM multi-classification problem, optimizing the parameters of SVM has become the key problem to improve the performance of the SVM multi-classification algorithm. In order to solve this problem, multi-chromosome genetic algorithm is proposed in this paper and used to optimize these parameters. In the SVM multi-classification decision tree, the algorithm constructs a chromosome for SVM parameter of each node and improves the corresponding rules of crossover and mutation in the genetic algorithm. The improved genetic algorithm optimizes the parameters of SVM in all nodes in the SVM multi-classification decision tree. The experimental results show that the SVM multi-classification decision tree algorithm using the multi-chromosome genetic algorithm has higher classification quality, compared with the traditional multi-SVM multi-classification algorithm.