基于遗传优化获取微阵列最佳分类规则

基于遗传编程(GP)提出一种最优规则遗传算法(BRGA)对分类规则进行优化的方法,获取最佳分类规则集,此算法可以调整分类器模型的相关参数,在适当增加迭代基础上大幅提高分类的精确度,具有相当的灵活性和可理解性.利用6个基因数据集检验了算法的性能.仿真结果表明,本文提出的算法与其他文献的方法相比,在具有较高分类精确度和稳定性前提下大幅降低了计算复杂度及冗余.

Obtaining Optimal Microarray Data Classification Rule by GA-based Optimizing

Based on Genetic Programming(GP),this paper proposed an approach called Best Rule Genetic Algorithm(BRGA) for optimizing classification rule,and gained the best classification rule set.This algorithm can adjust relevant parameters of classifier model,substantially improve the performance of classification by increasing appropriate iteration,therefore it has considerable flexibility and intelligibility.The performance of the proposed approach was evaluated by using six gene expression data sets through simulation.From the result,it is found that the proposed approach reduces computational complexity and redundancy with good classification accuracy and stability than approaches reported in other literatures so far.