Skip to main content

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].