非线性回归

# coding=utf-8
from sklearn.model_selection import train_test_split  # 这里是引用了交叉验证
from sklearn.linear_model import LinearRegression  # 线性回归
import numpy as np
from data_load import load_data
X,y = load_data()
# 训练数据
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2)
lin_reg = LinearRegression()
for i in range(2):
    lin_reg.fit(X_train, y_train)
feature_cols = ['so2', 'PM10', '悬挂高度', '电压等级']
B = list(zip(feature_cols, lin_reg.coef_))
print("系数 ", B)
# 预测
y_pred = lin_reg.predict(X_test)