/usr/include/BALL/QSAR/mlrModel.h is in libball1.4-dev 1.4.1+20111206-3.
This file is owned by root:root, with mode 0o644.
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*
* Copyright (C) 2009 Marcel Schumann
*
* This file is part of QuEasy -- A Toolbox for Automated QSAR Model
* Construction and Validation.
* QuEasy 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.
*
* QuEasy 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 program; if not, see <http://www.gnu.org/licenses/>.
*/
// -*- Mode: C++; tab-width: 2; -*-
// vi: set ts=2:
//
//
#ifndef MLRMODEL
#define MLRMODEL
#ifndef LMODEL
#include <BALL/QSAR/linearModel.h>
#endif
#ifndef QSAR_EXCEPTION
#include <BALL/QSAR/exception.h>
#endif
namespace BALL
{
namespace QSAR
{
class BALL_EXPORT MLRModel : public LinearModel
{
public:
/** @name Constructors and Destructors
*/
//@{
/** constructur
@param q QSAR-wrapper object, from which the data for this model should be taken */
MLRModel(const QSARData& q);
~MLRModel();
//@}
/** @name Accessors
*/
//@{
/** Starts multiple linear regression with the current data and saves the resulting linear combination of descriptors to training_result. \n
In order for this to work, descriptor_matrix MUST have more rows than columns, so that the matrix is invertible !! \n
If this is not the case, start a feature selection method before running train() ! */
virtual void train();
//@}
};
}
}
#endif // MLRMODEL
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