What are the best practices for building regression models?

What are the best practices for building regression models?

Some best practices include feature selection, data preprocessing, and validating your model with cross-validation.

Can you explain why feature selection is important?

Feature selection helps improve model performance by reducing overfitting and enhancing interpretability.

What techniques can I use for feature selection?

You can use techniques like Recursive Feature Elimination, Lasso Regression, or tree-based methods for feature selection.

How do I handle multicollinearity in my regression model?

You can address multicollinearity by removing highly correlated features, using regularization techniques, or combining features.