In this tutorial, we'll build a stump classifier and apply the AdaBoost algorithm. Our goal is to transform a weak classifier into something useful.
This lecture covers the first part of chapter 7 in Peter Harrington's book (Harrington, P. (2012). Machine Learning in Action. Shelter Island, NY: Manning) with some added commentary.
We'll discuss the implementation of the algorithm and how alpha scores
affect our decision making.
Then we will see a basic example of how to implement the algorithm.
