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Table 10 Coefficients for the ensemble logistic regression model trained in the YEAST gold standard

From: New methods for separating causes from effects in genomics data

Method (feature in the logistic regression model) Beta P-value
ANM -1.20 0.291
PNL -0.27 0.750
IGCI (Uniform/Entropy) -128.03 <0.0001
IGCI (Uniform/Integral) 135.07 <0.0001
IGCI (Gaussian/Entropy) 99.20 <0.0001
IGCI (Gaussian/Integral) -106.45 <0.0001
GPI-MML 1.15 0.578
ANM-MML -9.87 0.017
GPI 1.45 0.298
ANM-GAUSS 0.40 0.808
LINGAM 0.11 0.963
  1. Bold values correspond to coefficients that are statistically significant at 0.05 alpha level. We note that due to multicollinearity among the IGCI Uniform methods and among the IGCI Gaussian methods, care must be taken when interpreting the logistic regression coefficients [36].