# -*- coding: UTF-8 -*-
# 作者：huanhuilong
# 标题：SK-Learn 线性回归
# 描述：训练预测的基本套路


import numpy as np
from sklearn.linear_model import LinearRegression


def test():
    X = np.array([[1, 1], [1, 2], [2, 2], [2, 3]])
    y = np.dot(X, np.array([1, 2])) + 3

    reg = LinearRegression().fit(X, y)
    y_predict = reg.predict(np.array([[3, 5]]))
    print(y_predict)


if __name__ == '__main__':
    test()