What are some practical examples of ridge regularization?

What are some practical examples of ridge regularization?

Ridge regularization is commonly used in linear regression to prevent overfitting. For instance, in predicting housing prices, ridge regression can help manage multicollinearity among features.

Can you explain how it works in that context?

Sure! Ridge regularization adds a penalty equal to the square of the magnitude of coefficients to the loss function. This discourages large coefficients, thus stabilizing the model.

Are there specific industries where it's particularly useful?

Yes, it's widely used in finance for risk assessment models, in healthcare for predicting patient outcomes, and in marketing for customer segmentation.

How does it compare to Lasso regularization?

While both methods prevent overfitting, Lasso can shrink some coefficients to zero, effectively performing variable selection, whereas Ridge keeps all features but reduces their impact.