Multidimensional BSS/WSS Criterion for Modified SBFS Feature Selection Method in Tumor Classification
DEStech Transactions on Computer Science and Engineering(2018)
摘要
To avoid the defect of BSS/WSS criterion, we propose a multidimensional BSS/WSS feature selection criterion and modify the sequential backward floating selection (SBFS) algorithm to deal with the case where the covariance matrix is singular in this study. Then, we use support vector machine (SVM) to classify the gene expression data based on the proposed feature selection algorithm. The performance of the proposed approach is compared with BSS/WSS criterion and some other popular methods in feature selection and classification via the wellknown colon cancer and prostate datasets in microarray literature, which demonstrates that the proposed criterion can take into account genesu0027 joint discriminatory power, and the proposed feature selection method can obtain correct and informative gene subset for tumor classification.
更多查看译文
关键词
bss/wss criterion,selection,classification
AI 理解论文
溯源树
样例
![](https://originalfileserver.aminer.cn/sys/aminer/pubs/mrt_preview.jpeg)
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要