Statistical Learning #

Coure Description on UvA’s website

Topics #

• optimal prediction rules;
• cross-validation and the bootstrap;
• model selection and regularization methods (ridge and lasso);
• linear regression and classification;
• nonlinear models, splines and generalized additive models;
• tree-based methods, bagging and random forests.

Python programming from 2024 #

• Cross validation
• Linear regression
• Forward selection
• Information criteria
• Ridge and LASSO regression
• Principal component regression
• Logistic regression
• Linear and quadratic discriminant analysis
• Polynomial and spline regression
• Fitting classification and regression trees
• Random forest

Textbook #

James, G. et al. (2023). An Introduction to Statistical Learning - with Applications in Python.