prediction_utils.py 文件源码

def generate_model(self, regressor, qty_neighbors, algorithm, distance_type):
        """ Regressor Model Generation"""
        if regressor == "knn":
            return KNeighborsRegressor(n_neighbors=qty_neighbors, algorithm=algorithm, p=distance_type)
        elif regressor == "linear":
            return LinearRegression(fit_intercept=True) # copy_X=True, n_jobs=1, normalize=False
        elif regressor == "logistic":
            return LogisticRegression(class_weight='balanced')