ELM_MatlabClass is a fast MATLAB OOP implementation of Extreme Learning Machines as proposed by Huang et al.,

Huang, Guang-Bin, Qin-Yu Zhu, and Chee-Kheong Siew.
"Extreme learning machine: theory and applications." 
Neurocomputing 70.1 (2006): 489-501.

Huang, Guang-Bin, et al. "Extreme learning machine for regression and 
multiclass classification." Systems, Man, and Cybernetics, Part B: Cybernetics, 
IEEE Transactions on 42.2 (2012): 513-529.

If you want to use this package please cite

Taormina, Riccardo, and Kwok-Wing Chau. 
"Data-driven input variable selection for rainfall–runoff modeling using 
binary-coded particle swarm optimization and Extreme Learning Machines." 
Journal of Hydrology 529 (2015): 1617-1632.

for which it was initially developed.

This package contains:

1. ELM_MatlabClass.m, which is the class implementing the ELM;

2. example_CLASSIFICATION.m, which shows how to use ELM for binary classification;

3. example_REGRESSION.m, which shows how to use ELM for regression problems;

4. computeAccuracy.m, which computes classification accuracy of ELM;

5. computeR2.m, which computes the coefficient of determination(R^2);

6. README.MD, this file;

7. license.txt, the GNU GPL license.

The UCI datasets breast-cancer-wisconsin.data and data_akbilgic.csv are also included as they are used in the examples for CLASSIFICATION and REGRESSION, respectively. The datasets are available at http://archive.ics.uci.edu/ml/. Please refer to the UCI website for further information on the datasets.

Copyright 2015 Riccardo Taormina riccardo.taormina@gmail.com

This software is under the GNU General Public License. Please read the text version of the license included with the package (gpl.txt).

This file is part of ELM_MatlabClass.

ELM_MatlabClass is free software: you can redistribute 
it and/or modify it under the terms of the GNU General Public License 
as published by the Free Software Foundation, either version 3 of the 
License, or (at your option) any later version.     

ELM_MatlabClass is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

You should have received a copy of the GNU General Public License
along with  Matlab-Multi-objective-Feature-Selection.  
If not, see <http://www.gnu.org/licenses/>.