CAJ | 학술논문

提出一种结合最小熵信息度量和粒子群优化算法进行基因选取的方法。将每个粒子所代表的基因组合的信息度值作为该粒子的适应度函数值，通过粒子群的进化来获取最优基因子集，从而有利于实现样本分类。实验结果表明，该方法能够获取低冗余的信息基因，并在该方法选出的基因子集上，获得优于经典方法的分类准确率。
제출일충결합최소적신식도량화입자군우화산법진행기인선취적방법。장매개입자소대표적기인조합적신식도치작위해입자적괄응도함수치，통과입자군적진화래획취최우기인자집，종이유리우실현양본분류。실험결과표명，해방법능구획취저용여적신식기인，병재해방법선출적기인자집상，획득우우경전방법적분류준학솔。
In the paper we propose a method to select gene which combines minimum entropy information metric and particle swarm optimi-sation.It takes the informative degree value of gene combination represented by every particle as the fitness function value of the particle, and obtains optimal gene subsets through particle swarm evolution, therefore it is beneficial to the implementation of sample classification.Experi-ment result shows, this method can obtain gene information with low redundancy as well as the classification accuracy rate better than classic methods based on the gene subsets selected by it.