How can I improve my regression models?

How can I improve my regression models?

There are several ways to enhance your regression models, such as feature selection, regularization, and hyperparameter tuning. What specific area are you looking to improve?

I'm interested in feature selection. What techniques do you recommend?

You can use techniques like Recursive Feature Elimination (RFE), Lasso regression, or tree-based methods like Random Forest for feature selection. Have you tried any of these?

I've used Lasso regression. What about regularization?

Regularization techniques like L1 (Lasso) and L2 (Ridge) can help prevent overfitting by adding a penalty to the loss function. Would you like to know how to implement these?