def cric__lasso ( ) : model = sklearn . linear_model . LogisticRegression ( penalty = "l1" , C = 0.002 ) # we want to explain the raw probability outputs of the trees model . predict = lambda X : model . predict_proba ( X ) [ : , 1 ] return model
stackoverflow python logistic regression lasso
Lasso Regression
def cric__lasso():
    """ Lasso Regression
    """
    model = sklearn.linear_model.LogisticRegression(penalty="l1", C=0.002)

    # we want to explain the raw probability outputs of the trees
    model.predict = lambda X: model.predict_proba(X)[:,1]
    
    return model