Ensemble Toolbox

This toolbox provides some combination methods to fuse an ensemble of classifiers

Please cite at least one of the following papers if you like to use this toolbox:
+ M.A. Bagheri, Gh. Montazer, and E. Kabir, “A Subspace Approach to Error-Correcting Output Coding”,
Pattern Recognition Letters, vol. 34, pp. 176–184, 2013
+ M.A. Bagheri, Q. Gao and S. Escalera, “Rough Set Subspace Error Correcting Output Codes”,
in Proc. IEEE International Conf on Data Mining, Brussels, Belgium, 2012

For better understanding of the toolbox, reading the following references is strongly recommended
[1] R. Polikar, "Ensemble based systems in decision making," IEEE Circuits and Systems Magazine, vol. 6, pp. 21-45, 2006.
[2] L. I. Kuncheva, Combining Pattern Classifiers: Methods and Algorithms. New York, NY: Wiley, 2004.

%%%% How to use
%% You should run the Main_Ensemble.m file

%% Dataset
*** You can use any of the included datasets (taken from UCI ) or your own dataset;
*** To use your dataset, you should put the dataset in the Datasets folder
*** The data should be stored in one text file. You can save data in "Excel > Save as Text (Tab Delimited)"
*** The dataset should be in a Matrix format;
*** number of rows is equal to the number of samples
*** Number of columns is equal to the number of features + 1
*** The last column is the Target (Label) column of samples