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Table 6 p-values obtained from Wilcoxon signed test comparing DKL and mDKL with other formulations for the von Mering data set.

From: Adaptive diffusion kernel learning from biological networks for protein function prediction

Algorithm DKL mDKL
uBaseline 5.849E-7 2.966E-7
rBaseline 1.510E-10 1.038E-10
eBaseline 4.268E-10 2.863E-10
DKL 1.000 6.531E-2
DKLKL 3.776E-1 1.669E-1
DKL KL u MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGaeeiraqKaee4saSKaeeitaW0aa0baaSqaaiabbUealjabbYeambqaaiabbwha1baaaaa@32FA@ 6.870E-11 3.193E-11
mDKL 6.531E-2 1.000
mDKLKL 5.971E-2 1.637E-1
mDKL KL u MathType@MTEF@5@5@+=feaafiart1ev1aaatCvAUfKttLearuWrP9MDH5MBPbIqV92AaeXatLxBI9gBaebbnrfifHhDYfgasaacPC6xNi=xH8viVGI8Gi=hEeeu0xXdbba9frFj0xb9qqpG0dXdb9aspeI8k8fiI+fsY=rqGqVepae9pg0db9vqaiVgFr0xfr=xfr=xc9adbaqaaeGaciGaaiaabeqaaeqabiWaaaGcbaGaeeyBa0MaeeiraqKaee4saSKaeeitaW0aa0baaSqaaiabbUealjabbYeambqaaiabbwha1baaaaa@345B@ 3.193E-11 8.252E-12
  1. For the von Mering data set, each algorithm produces an ROC vector consisting of ROC values over each task. We use Wilcoxon signed test to test the difference of the paired data. The null hypothesis of this test is that the ROC vectors produced by the two compared algorithms have the common median. The numbers reported in this table are the p-values that represent the probabilities that the null hypothesis is true. Typically, the null hypothesis is rejected if p < 0.05.