Online Training Workshop on Machine Learning for Economic Analysis - May 2024 - Day 3
Objectives: The objective of the workshop is to train participants in the main Machine Learning (ML) methods in the specific context of economic analysis. The training will focus on supervised and semi-supervised classification techniques. In this context, the aim will be to propose a reflection on the existence of a trade-off between the interpretability and predictive performance of models derived from ML algorithms. This intermediate-level course is aimed at participants with notions of statistical learning and basic notions of programming.
Knowledge transfer: the course will combine a general presentation of ML with a more detailed presentation of a few methods commonly used in the context of economic analysis.
Day 3 (May 27)
Supervised learning methods: Boosting
Principles of boosting methods.
Advantages and limitations of boosting.
AdaBoost method.
Gradient Boosting and XGBoost methods.
Supervised learning methods: SVM
Introduction to the support vector machine (SVM).
Formalization of the SVM.
The kernel trick.
Support Vector Regression (SVR).