Prepare

Due: October 8, 2024

Learning objectives

• Identify the benefits of a simplified machine learning model
• Consider how dimension reduction can be used to reduce the number of features in a model
• Examine how tree-based and regularization models naturally incorporate feature selection
• Implement feature selection and reduction techniques using {tidymodels}

Preparations

📖 Read

• TMWR ch 16.6 - Dimensionality reduction (Modeling)
• ISLR ch 6 - Linear model selection and regularization - read sections 6.2-.3. We skip 6.1 mainly because these methods are intractable for datasets with more than a trivial number of features.