如何打印多元线性回归模型(r2等)的结果摘要- SciKitLearn模型与Statsmodels

import numpy as np
import pandas as pd
import statsmodels.api as sm
from sklearn.linear_model import LinearRegression
from sklearn.metrics import r2_score

# 假设我们有三个自变量 x1, x2, x3 和一个因变量 y
x1 = [1, 2, 3, 4, 5]
x2 = [2, 4, 6, 8, 10]
x3 = [3, 6, 9, 12, 15]
y = [5, 10, 15, 20, 25]

# 将数据组合成一个 DataFrame
data = pd.DataFrame({'x1': x1, 'x2': x2, 'x3': x3, 'y': y})

# 添加常数列作为截距
data_with_intercept = sm.add_constant(data[['x1', 'x2', 'x3']])

# 拟合线性回归模型
model = sm.OLS(data['y'], data_with_intercept)
results = model.fit()

# 打印结果摘要
print(results.summary())

# 创建线性回归模型对象
model = LinearRegression()

# 拟合线性回归模型
model.fit(data[['x1', 'x2', 'x3']], data['y'])

# 预测因变量
y_pred = model.predict(data[['x1', 'x2', 'x3']])

# 计算R²分数
r2 = r2_score(data['y'], y_pred)

# 打印R²分数
print("R²分数:", r2)