/usr/include/BALL/QSAR/regressionModel.h is in libball1.4-dev 1.4.1+20111206-3.
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1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 | /* regressionModel.h
*
* 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 REGRESSION
#define REGRESSION
#ifndef MODELH
#include <BALL/QSAR/Model.h>
#endif
#ifndef REGVALIDATION
#include <BALL/QSAR/regressionValidation.h>
#endif
#include <fstream>
namespace BALL
{
namespace QSAR
{
class BALL_EXPORT RegressionModel : public Model
{
public:
/** @name Constructors and Destructors
*/
//@{
/** constructur,
@param q QSAR-wrapper object, from which the data for this model should be taken */
RegressionModel(const QSARData& q);
~RegressionModel();
virtual void operator=(const RegressionModel& m);
//@}
/** @name Accessors
*/
//@{
/** a ModelValidation object, that is used to validate this model and that will contain the results of the validations */
RegressionValidation* validation;
/** returns a const pointer to the matrix containing the coefficients obtained by Model.train() */
const BALL::Matrix<double>* getTrainingResult() const;
virtual void saveToFile(string filename);
virtual void readFromFile(string filename);
void show();
//@}
protected:
/** @name Attributes
*/
//@{
/** BALL::Matrix<double> containing the coefficients obtained by Model.train().\n
raining_result will have the following dimensions for the different types of models, with m=no of descriptors and c=no of modelled activities (=no of columns of Model.Y) : \n
LinearModel : mxc \n
KernelModel : nxc \n
ALLModel : mxc \n
FitModel : mxc \n
SVMModel : m x (c*no of classes) \n
SVRModel : m x (c*no of classes) */
BALL::Matrix<double> training_result_;
// RowVector holding the regression constants (one value for each feature)
Vector<double> offsets_;
//@}
/** @name Input and Output. The following methods can be used to implement the functions saveToFile() and readFromFile() in final classes derived from this base-class
*/
//@{
virtual void calculateOffsets() = 0;
void readDescriptorInformationFromFile(std::ifstream& in, int no_descriptors, bool transformation, int no_coefficients);
void saveDescriptorInformationToFile(std::ofstream& out);
//@}
friend class RegressionValidation;
};
}
}
#endif // REGRESSION
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