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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 NORMALIZE_INC
#define NORMALIZE_INC
#include "general.h"
namespace Torch {
/** Compute means and variances for normalizing a matrix.
Returns in
\begin{itemize}
\item #mean_buff# means table of each columns of #tab#.
\item #std_buff# the standard deviations table.
\end{itemize}
Note: the memory allocation is not made by this function.
#n_ex# is the number of examples in #tab#, and #n_dim# is
the dimension of each example.
@author Ronan Collobert (collober@iro.umontreal.ca)
*/
void MSTDVNormalize(real **tab, real *mean_buff, real *std_buff, int n_ex, int n_dim);
/** Compute means and variances for normalizing a \emph{sparse} matrix.
Returns in
\begin{itemize}
\item #mean_buff# means table of each columns of #tab#.
\item #std_buff# the standard deviations table.
\end{itemize}
Note: the memory allocation is not made by this function.
#n_ex# is the number of examples in #tab#, and #n_dim# is
the dimension of each example.
@author Ronan Collobert (collober@iro.umontreal.ca)
*/
void MSTDVSparseNormalize(sreal **tab, real *mean_buff, real *std_buff, int n_ex, int n_dim);
}
#endif
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