python绘制lasso回归路径图

可以使用scikit-learn和matplotlib库来绘制lasso回归路径图，具体步骤如下：

1. 导入必要的库

from sklearn.linear_model import Lasso
import matplotlib.pyplot as plt
import numpy as np

2. 定义数据集

# 生成随机数据
np.random.seed(42)
n_samples, n_features = 50, 100
X = np.random.randn(n_samples, n_features)
y = np.random.randn(n_samples)

3. 初始化Lasso模型，设置alpha参数

model = Lasso(alpha=0.1)

4. 计算lasso回归路径

alphas = np.logspace(-3, 0, 100)
coefs = []
for a in alphas:
    model.set_params(alpha=a)
    model.fit(X, y)
    coefs.append(model.coef_)

5. 绘制lasso回归路径图

plt.figure(figsize=(10, 6))
ax = plt.gca()
ax.plot(alphas, coefs)
ax.set_xscale('log')
ax.set_xlim(ax.get_xlim()[::-1])  # reverse axis
plt.xlabel('alpha')
plt.ylabel('weights')
plt.title('Lasso coefficients as a function of the regularization')
plt.axis('tight')
plt.show()

绘制的图形将显示Lasso回归路径，其中横轴为alpha值，纵轴为权重。