Best performance for a C value among the kernel is presented. Highest performances are highlighted, along with the feature set and kernel that achieved it. Evaluation Metrics: Accuracy (ACC), Sensitiv

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Results using different PSO algorithms for SVM with stepwise regression.

SVM支持向量机

特征选择

Results using different PSO algorithms for SVM with stepwise regression.

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Comparison of the performance of three kernel functions of SVM.

SVM支持向量机

分类模型评估

radial basis kernel function: Gaussian kernel; AUC: area under ROC curve; Spe: specificity; Pre: precision; Sen: sensitivity; F1: F-measure; MCC: Matthews correlation coefficient; ACC: accuracy.

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Performances of SVM-based method on promiscuous domains.

蛋白质相互作用

SVM支持向量机

Definition of the best prediction can be found at the caption of Table 2. The degree value of each domain can be found at Table 5.

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