def cric__ridge():
    """ Ridge Regression
    """
    model = sklearn.linear_model.LogisticRegression(penalty="l2")

    # we want to explain the raw probability outputs of the trees
    model.predict = lambda X: model.predict_proba(X)[:,1]
    
    return model
def cric__ridge ( ) : model = sklearn . linear_model . LogisticRegression ( penalty = "l2" ) model . predict = lambda X : model . predict_proba ( X ) [ : , 1 ] return model
Ridge Regression