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:
ELM_MatlabClass.m, which is the class implementing the ELM;
example_CLASSIFICATION.m, which shows how to use ELM for binary classification;
example_REGRESSION.m, which shows how to use ELM for regression problems;
computeAccuracy.m, which computes classification accuracy of ELM;
computeR2.m, which computes the coefficient of determination(R^2);
README.MD, this file;
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.
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/>.
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