What is the difference between Ridge and Lasso regression?

What is the difference between Ridge and Lasso regression?

Ridge regression adds a penalty equal to the square of the magnitude of coefficients, while Lasso regression adds a penalty equal to the absolute value of coefficients.

When should I use Ridge over Lasso?

Use Ridge when you have many features and want to keep them all, as it tends to shrink coefficients but not eliminate them.

And when is Lasso more appropriate?

Lasso is better when you want feature selection, as it can shrink some coefficients to zero, effectively removing them.

Can I use both Ridge and Lasso together?

Yes, you can use Elastic Net, which combines both Ridge and Lasso penalties to balance their strengths.

What are some practical applications of these techniques?

Both techniques are widely used in machine learning for regression tasks, especially in high-dimensional datasets.