python线性回归方程
时间: 2023-11-18 13:04:10 浏览: 41
以下是使用Python进行线性回归分析的步骤和代码示例:
1. 导入所需的库和数据集
```python
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
%matplotlib inline
# 读取数据集
data = pd.read_csv('data.csv')
```
2. 确定自变量和因变量
```python
# 确定自变量和因变量
X = data['自变量'].values.reshape(-1,1)
y = data['因变量'].values.reshape(-1,1)
```
3. 划分训练集和测试集
```python
from sklearn.model_selection import train_test_split
# 划分训练集和测试集
X_train, X_test, y_train, y_test = train_test_split(X, y, test_size=0.2, random_state=0)
```
4. 创建线性回归模型并进行训练
```python
from sklearn.linear_model import LinearRegression
# 创建线性回归模型
regressor = LinearRegression()
# 训练模型
regressor.fit(X_train, y_train)
```
5. 进行预测并可视化结果
```python
# 进行预测
y_pred = regressor.predict(X_test)
# 可视化结果
plt.scatter(X_train, y_train, color='red')
plt.plot(X_train, regressor.predict(X_train), color='blue')
plt.title('线性回归')
plt.xlabel('自变量')
plt.ylabel('因变量')
plt.show()
```