MSERBFNet.h File Reference

Offers the functions to create and to work with radial basis function networks and to train it with the mean squared error. This combination provides more computational efficiency compared to using the class MeanSquaredError. More...

#include "ReClaM/RBFNet.h"
#include "Array/Array.h"

Go to the source code of this file.

Classes

class MSERBFNet

Offers the functions to create and to work with radial basis function networks and to train it with the mean squared error. This combination provides more computational efficiency compared to using the class MeanSquaredError. More...

Detailed Description

Author:: C. Igel

Date:: 2001

Copyright (c) 1999-2001:: Institut für Neuroinformatik
Ruhr-Universität Bochum
D-44780 Bochum, Germany
Phone: +49-234-32-25558
Fax: +49-234-32-14209
eMail: Shark-admin@neuroinformatik.ruhr-uni-bochum.de
www: http://www.neuroinformatik.ruhr-uni-bochum.de

Project:: ReClaM

This file is part of ReClaM. This library 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 2, or (at your option) any later version.

This library 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 this library; if not, write to the Free Software Foundation, Inc., 675 Mass Ave, Cambridge, MA 02139, USA.

Definition in file MSERBFNet.h.


Classes
class	MSERBFNet
	Offers the functions to create and to work with radial basis function networks and to train it with the mean squared error. This combination provides more computational efficiency compared to using the class MeanSquaredError. More...