How can I visualize the results of a Lasso regression?

How can I visualize the results of a Lasso regression?

You can visualize Lasso regression results using plots like coefficient paths or residual plots. Would you like to see an example?

Yes, please show me how to create a coefficient path plot.

To create a coefficient path plot, you can use libraries like Matplotlib or Seaborn in Python. Would you like a code snippet?

That would be great! What does the code look like?

Here's a simple example:

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

# Sample data
X = np.random.rand(100, 10)
y = np.random.rand(100)

# Lasso regression with cross-validation
lasso = LassoCV(alphas=np.logspace(-4, 4, 100)).fit(X, y)

# Plotting the coefficients
plt.plot(lasso.coef_)
plt.title('Lasso Coefficients Path')
plt.xlabel('Features')
plt.ylabel('Coefficient Value')
plt.show()

This will give you a visual representation of the coefficients.