Ensemble Learning Toolbox
A simple toolbox for the creation of ensembles of classifiers and regressors.
You are now following this Submission
- You will see updates in your followed content feed
- You may receive emails, depending on your communication preferences
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.
Cite As
@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.
General Information
- Version 1.0.0 (9.1 KB)
-
View License on GitHub
MATLAB Release Compatibility
- Compatible with any release
Platform Compatibility
- Windows
- macOS
- Linux
Versions that use the GitHub default branch cannot be downloaded
| Version | Published | Release Notes | Action |
|---|---|---|---|
| 1.0.0 | First complete version available. |
||
| 0.7 | Multi-class functionality added. |
||
| 0.5 | Added regression functionality. |
||
| 0.4 | Scalability fix. |
||
| 0.3 | A new demonstration code has been added to show the toolbox's versatility. |
||
| 0.2 | Simplified access to class parameters. |
||
| 0.1 |
