Ensemble Learning Toolbox
This is a simple class/toolbox for classification and regression ensemble learning.
It enables the user to manually create heterogeneous, majority voting, weighted majority voting, mean, and stacking ensembles with MATLAB's "Statistics and Machine Learning Toolbox" classification models.
Version 1.0.0 also adds boosting, bagging, random subspace, and "random forest" training approaches.
Citation pour cette source
@article{ribeiro2020ensemble, title={Ensemble Learning Toolbox: Easily Building Custom Ensembles in MATLAB}, author={Victor Henrique Alves Ribeiro and Gilberto Reynoso-Meza}, year={in review} }
Victor Henrique Alves Ribeiro and Gilberto Reynoso-Meza (In review). Ensemble Learning Toolbox: Easily Building Custom Ensembles in MATLAB.
Compatibilité avec les versions de MATLAB
Plateformes compatibles
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- AI and Statistics > Statistics and Machine Learning Toolbox > Classification > Classification Ensembles >
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Version | Publié le | Notes de version | |
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1.0.0 | First complete version available. |
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0.7 | Multi-class functionality added. |
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0.5 | Added regression functionality. |
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0.4 | Scalability fix. |
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0.3 | A new demonstration code has been added to show the toolbox's versatility. |
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0.2 | Simplified access to class parameters. |
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0.1 |
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