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.
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.
MATLAB Release Compatibility
Platform Compatibility
Windows macOS LinuxCategories
- AI and Statistics > Statistics and Machine Learning Toolbox > Classification > Classification Ensembles >
Tags
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.
examples
src
Versions that use the GitHub default branch cannot be downloaded
Version | Published | Release Notes | |
---|---|---|---|
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 |
|