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// Copyright (C) 2002 Ronan Collobert (collober@iro.umontreal.ca)
//
//
// This file is part of Torch. Release II.
// [The Ultimate Machine Learning Library]
//
// Torch 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 of the License, or
// (at your option) any later version.
//
// Torch 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 Torch; if not, write to the Free Software
// Foundation, Inc., 59 Temple Place, Suite 330, Boston, MA 02111-1307 USA
#ifndef STOCHASTIC_GRADIENT_INC
#define STOCHASTIC_GRADIENT_INC
#include "Optimizer.h"
#include "random.h"
namespace Torch {
/** Stochastic Gradient Optimizer for GMTrainer
Options:
\begin{tabular}{lcll}
"end accuracy" & real & end accuracy & [0.0001]\\
"learning rate" & real & learning rate & [0.01]\\
"learning rate decay" & real & learning rate decay & [0]\\
"max iter" & int & maximum number of iterations & [-1]
\end{tabular}
@see GMTrainer
@author Ronan Collobert (collober@iro.umontreal.ca)
*/
class StochasticGradient : public Optimizer
{
public:
real learning_rate;
real learning_rate_decay;
real end_accuracy;
int max_iter;
//-----
///
StochasticGradient();
virtual void train(List *measurers);
//-----
virtual ~StochasticGradient();
};
}
#endif
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