In this lesson we learn about discriminant analysis, a popular classification algorithm for predicting response variables with two or more levels.

We will also cover the K-Nearest Neighbor (KNN) algorithm, which can be used for regression or classification tasks. The KNN algorithm contains model hyperparameters - these are parameters of a model that cannot be estimated directly from our training data and must be estimated with a process known as hyperparameter tuning.

The R tutorial in this lesson will introduce how to fit these models with tidymodels as well as how to perform hyperparameter tuning.

# Next Steps

Please head over to the R tutorial where you will learn how to fit discriminant analysis and KNN models with the tidymodels package.