Lecture 12 : Bayes Classifier I

The lecture introduces the Bayes classifier, explaining its advantages over decision trees by utilizing statistical properties of training sets. Through an example involving fish classification, it discusses determining a boundary length for accurate classification, illustrating how to find this optimal boundary using class conditional distributions and addressing potential biases in population data.