Multi-Class Classification: Approaches and Boundaries

This lecture covers the strategies for multi-class classification, including the one-against-all and one-on-one approaches, and the concept of decision boundaries in the context of machine learning. It explains how to train multiple binary classifiers to classify data into multiple classes and the implications of decision boundaries in distinguishing between classes.