首页> 外文OA文献 >Figure 10: Outliers plots: (A) boxplot with the results of the best three methods (ENET, FSMKL and SVM-RFE) with and without the outliers. *, Statistically significant difference with a p-value < 2.2 × 10−16 according to a pairwise Wilcoxon test; **, Statistically significant difference according to a non-parametric Friedman test with Iman and Davenport correction with a p-value < 1.92 × 10−41. At the bottom of the panel, a median-based contrast estimation heatmap. In (B) the residues are plotted by coloring each of them according to the category to which the image belongs.
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Figure 10: Outliers plots: (A) boxplot with the results of the best three methods (ENET, FSMKL and SVM-RFE) with and without the outliers. *, Statistically significant difference with a p-value < 2.2 × 10−16 according to a pairwise Wilcoxon test; **, Statistically significant difference according to a non-parametric Friedman test with Iman and Davenport correction with a p-value < 1.92 × 10−41. At the bottom of the panel, a median-based contrast estimation heatmap. In (B) the residues are plotted by coloring each of them according to the category to which the image belongs.

机译:图10:异常值绘图:(a)Boxplot与具有和没有异常值的最佳三种方法(ENET,FSMK1和SVM-RFE)的结果。 *,根据双氟硅酮试验,与p值<2.2×10-16的统计学上有显着差异; **,根据非参数弗里德曼测试的统计学意义差异,具有P值<1.92×10-41的IMAN和DAVENPORT校正。在面板的底部,基于中位的对比度估计热图。在(b)中,通过根据图像所属的类别着色,通过着色它们来绘制残留物。

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