Ensemble Learning Toolbox

Version 1.0.0 (9.1 KB) by Victor Henrique Alves Ribeiro
A simple toolbox for the creation of ensembles of classifiers and regressors.
5.0
(7)
1.9K Downloads
Updated 13 May 2020
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.

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

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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

To view or report issues in this GitHub add-on, visit the GitHub Repository.
To view or report issues in this GitHub add-on, visit the GitHub Repository.