Machine Learning with R, the tidyverse, and mlr

Chapter 5. Classifying by maximizing separation with discriminant analysis

This chapter covers

• Understanding linear and quadratic discriminant analysis
• Building discriminant analysis classifiers to predict wines

Discriminant analysis is an umbrella term for multiple algorithms that solve classification problems (where we wish to predict a categorical variable) in a similar way. While there are various discriminant analysis algorithms that learn slightly differently, they all find a new representation of the original data that maximizes the separation between the classes.

Recall from chapter 1 that predictor variables are the variables we hope contain the information needed to make predictions on new data. Discriminant function analysis algorithms ...