33  Supervised Learning

33.1 Learning objectives

  • Translate a research question into a supervised learning workflow.
  • Separate preprocessing, model selection, and performance evaluation.
  • Interpret predictions, performance estimates, and model explanations.

33.2 From research question to model

33.3 Baseline model

33.4 Preprocessing and data leakage

33.5 Resampling for model selection

33.6 Hyperparameter tuning

33.7 Resampling for model evaluation

33.8 Assessing model performance

33.9 Bias, variance, and model complexity

33.10 Interpretation and explainability

33.11 Demo: Supervised learning with rtemis

33.12 Hands-on practice

33.13 Checkpoint

33.14 Further study