Machine Learning 3.2 - Linear Discriminant Analysis (LDA) and Quadratic Discriminant Analysis (QDA)

We will cover classification models in which we estimate the probability distributions for the classes. We can then compute the likelihood of each class for a new observation, and then assign the new observation to the class with the greatest likelihood. These maximum likelihood methods, such as the LDA and QDA methods you will see in this section, are often the best methods to use on data whose classes are well-approximated by standard probability distributions. This material complements pp. 138-149 of An Introduction to Statistical Learning (http://faculty.marshall.usc.edu/gareth-james/ISL/index.html).