cdt/causality/pairwise/ANM.py
def predict_proba(self, a, b, **kwargs):
        """Prediction method for pairwise causal inference using the ANM model.

        Args:
            a (numpy.ndarray): Variable 1
            b (numpy.ndarray): Variable 2

        Returns:
            float: Causation score (Value : 1 if a->b and -1 if b->a)
        """
        a = scale(a).reshape((-1, 1))
        b = scale(b).reshape((-1, 1))

        return self.anm_score(b, a) - self.anm_score(a, b)
def predict_proba(self, a, b, **kwargs):
        """Prediction method for pairwise causal inference using the ANM model.

        Args:
            a (numpy.ndarray): Variable 1
            b (numpy.ndarray): Variable 2

        Returns:
            float: Causation score (Value : 1 if a->b and -1 if b->a)
        """
        a = scale(a).reshape((-1, 1))
        b = scale(b).reshape((-1, 1))

        return self.anm_score(b, a) - self.anm_score(a, b)
def predict_proba ( self , a , b , * * kwargs ) : a = scale ( a ) . reshape ( ( - 1 , 1 ) ) b = scale ( b ) . reshape ( ( - 1 , 1 ) ) return self . anm_score ( b , a ) - self . anm_score ( a , b )
Prediction method for pairwise causal inference using the ANM model.

        Args:
            a (numpy.ndarray): Variable 1
            b (numpy.ndarray): Variable 2

        Returns:
            float: Causation score (Value : 1 if a->b and -1 if b->a)
Prediction method for pairwise causal inference using the ANM model .