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).
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Mo Chen (2024). Adaboost (https://www.mathworks.com/matlabcentral/fileexchange/55880-adaboost), MATLAB Central File Exchange. Recuperado .
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Windows macOS LinuxCategorías
- AI and Statistics > Statistics and Machine Learning Toolbox > Classification >
- Control Systems > Predictive Maintenance Toolbox >
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Inspirado por: Pattern Recognition and Machine Learning Toolbox
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adaboost/
Versión | Publicado | Notas de la versión | |
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1.0.0.0 |