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Multiple SVM-RFE for multi-class gene selection on DNA Microarray data

机译:DNA微阵列数据对多级基因选择的多种SVM-RFE

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This paper presents a new multi-class gene selection and classification method based on multiple support vector machine recursive feature elimination (SVM-RFE). For a multi-class DNA microarray problem, we solve it as multiple binary classification problems. First, the one-versus-all method is used to decompose the multi-class task into multiple binary problems. Second, an SVM-RFE is adopted to select genes for each binary problem. Then, an SVM classifier is used to train the selected gene data for a binary problem. Finally, we combine the outputs of multiple SVM classifiers. Experimental results on three DNA Microarray datasets show that the proposed method achieves higher classification accuracy.
机译:本文介绍了一种基于多级支持向量机递归特征消除(SVM-RFE)的多级基因选择和分类方法。对于多级DNA微阵列问题,我们将其解决了多个二进制分类问题。首先,一个与之所有方法用于将多级任务分解为多个二进制问题。其次,采用SVM-RFE为每个二进制问题选择基因。然后,使用SVM分类器来训练所选择的基因数据进行二进制问题。最后,我们组合了多个SVM分类器的输出。三个DNA微阵列数据集的实验结果表明,该方法的分类精度较高。

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