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Ensemble Learning Toolbox

A simple toolbox for the creation of ensembles of classifiers and regressors.

41 Downloads

Updated 13 May 2020

GitHub view license on GitHub

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.

Comments and Ratings (5)

Thank you for your sharing~~

py chang

Thank you for your sharing!

thanks for your effort, however, i am trying to apply different CNNs such as lenet , alexnet, and vggnet . if i want to apply majority voting could u explain how to run that?
thanks

liguiyi

Updates

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.

MATLAB Release Compatibility
Created with R2019b
Compatible with any release
Platform Compatibility
Windows macOS Linux