Supervised Learning: Classification Algorithms

This lecture covers supervised learning in financial econometrics, focusing on classification algorithms. It explains the concepts of generative and discriminative classification, including examples like Naive Bayes and Logistic Regression. The lecture also delves into model assessment, approaches to control overfitting, and the comparison between generative and discriminative classifiers. Various classification methods such as k-nearest neighbors, Linear Discriminant Analysis, and Decision Trees are discussed, along with their applications and performance evaluation techniques like confusion matrices and ROC curves.