Chapter 7. Improving classification with the AdaBoost meta-algorithm
This chapter covers
- Combining similar classifiers to improve performance
- Applying the AdaBoost algorithm
- Dealing with classification imbalance
If you were going to make an important decision, you’d probably get the advice of multiple experts instead of trusting one person. Why should the problems you solve with machine learning be any different? This is the idea behind a meta-algorithm. Meta-algorithms are a way of combining other algorithms. We’ll focus on one of the most popular meta-algorithms called AdaBoost. This is a powerful tool to have in your toolbox because AdaBoost is considered by some to be the best-supervised learning algorithm.
Get Machine Learning in Action now with the O’Reilly learning platform.
O’Reilly members experience books, live events, courses curated by job role, and more from O’Reilly and nearly 200 top publishers.
