📋 Linear Regression Decision Cards

This section contains decision cards that guide key choices when building and refining linear regression models.

These resources help analysts evaluate model complexity, select appropriate transformation strategies, and balance model fit with interpretability using statistically sound methods.

📂 Available Decision Cards

• 📋 AIC vs BIC Decision Card — Understand when to prioritize Akaike Information Criterion (AIC) vs Bayesian Information Criterion (BIC) for model selection.
• 📋 Linear Feature Transformation Trigger Card — Identify when feature transformations are necessary to meet model assumptions.
• 📋 Regularization Decision Card — Choose between Lasso, Ridge, and ElasticNet regularization techniques for improved generalization.