文化算法框架下混合群智能算法的肿瘤信息基因选择

为了消除与分类无关和冗余基因,以提高基因的分类精度和效率,提出一种文化算法框架下混合群智能算法的肿瘤信息基因选择方法.首先采用ReliefF算法初选基因子集,然后利用文化算法框架下混合群智能算法选择最优的信息基因,最后在3个标准肿瘤信息基因数据集对其性能进行测试.仿真结果表明,文化算法框架下混合群智能算法可以有效去掉无用的噪声基因,降低计算复杂度,分类精度均可以达到100%,具有较好的实际应用价值.

Cancer gene selection by hybrid swarm algorithm based on cultural algorithm

In order to eliminate irrelevant and redundant genes and improve the classification accuracy and efficiency, this paper proposed a cancer gene selection method by hybrid swarm algorithm based on cultural algorithm. Firstly, ReliefF algorithm is used to select the primary gene subset, and then hybrid swarm algorithm based on cultural algorithm is used to select the optimal information gene. Finally, the performance is tested by three standard tumor information gene data set. The simulation results show that the proposed method can remove noise and useless and reduce the computing complexity, the classification accuracy can reach 100%, and has good practical value.