Ensemble Methods for Machine Learning
by Gautam Kunapuli
- Github: https://github.com/gkunapuli/ensemble-methods-notebooks
- MEAP began July 2020
- Publication in Spring 2023
- ISBN 9781617297137
- 350 pages (estimated)
- printed in black & white
Reading Notes:
Part 1: HE BASICS OF ENSEMBLES
1. Ensemble Learning: Hype or Halleleujah?
Part 2: ESSENTIAL ENSEMBLE METHODS
2. Homogeneous Parallel Ensembles: Bagging and Random Forests
- Heterogeneous Parallel Ensembles: Combining Strong Learners
- Sequential Ensembles: Boosting
- Sequential Ensembles: Gradient Boosting
- Sequential Ensembles: Newton Boosting
Part 3: ENSEMBLES IN THE WILD: ADAPTING ENSEMBLE METHODS TO YOUR DATA
- Learning with Continuous and Count Labels
- Learning with Categorical Features
- Explaining Your Ensembles
- Further Reading
