3  Machine learning and nonparametric methods 🚧

Learning objectives

After reading this chapter, you should be able to:

  • Apply fundamental supervised learning concepts to climate hazard assessment problems
  • Understand nonparametric and semiparametric methods for flexible modeling
  • Critically evaluate machine learning applications in climate risk literature
  • Understand bias-variance tradeoffs and model validation approaches

3.1 Essential machine learning concepts

  1. Supervised and unsupervised learning paradigms
  2. Parametric vs nonparametric methods
  3. Bias-variance tradeoff and regularization
  4. Cross-validation and model selection
  5. Tree-based methods and ensemble learning

Further reading