This is a Matlab implementation of Adaboost for binary classification. The weak learner is kmeans. The reason why this weaker learner is used is that this is the one of simplest learner that works for both discrete and continues data. I make the code very succinct so that it is easy to read and learn how Adaboost works.
This package is now a part of the PRML toolbox (http://www.mathworks.com/matlabcentral/fileexchange/55826-pattern-recognition-and-machine-learning-toolbox).
Cite As
Mo Chen (2024). Adaboost (https://www.mathworks.com/matlabcentral/fileexchange/55880-adaboost), MATLAB Central File Exchange. Retrieved .
MATLAB Release Compatibility
Platform Compatibility
Windows macOS LinuxCategories
- AI and Statistics > Statistics and Machine Learning Toolbox > Classification >
- Control Systems > Predictive Maintenance Toolbox >
Tags
Acknowledgements
Inspired by: Pattern Recognition and Machine Learning Toolbox
Community Treasure Hunt
Find the treasures in MATLAB Central and discover how the community can help you!
Start Hunting!Discover Live Editor
Create scripts with code, output, and formatted text in a single executable document.
adaboost/
Version | Published | Release Notes | |
---|---|---|---|
1.0.0.0 |