/usr/include/BALL/QSAR/allModel.h is in libball1.4-dev 1.4.1+20111206-3.
This file is owned by root:root, with mode 0o644.
The actual contents of the file can be viewed below.
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 | /* allModel.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 ALLMODEL
#define ALLMODEL
#ifndef NLMODEL
#include <BALL/QSAR/nonlinearModel.h>
#endif
namespace BALL
{
namespace QSAR
{
/** class for automated lazy learning (ALL-QSAR) */
class BALL_EXPORT ALLModel : public NonLinearModel
{
public:
/** @name Constructors and Destructors
*/
//@{
ALLModel(const QSARData& q, double kw=4);
~ALLModel();
//@}
/** @name Accessors
*/
//@{
void setKw(double kw);
virtual Vector<double> predict(const vector<double>& substance, bool transform=1);
/** automated lazy learning does not have a seperate training step */
void train(){};
/** Tries to find the optimal kernel width for the current data. Therefore some training data must have been read by the connected QSARData object before running this method. */
virtual bool optimizeParameters(int d, int no_steps);
/** returns the current kernel width */
double getKw();
virtual void setParameters(vector<double>& v);
virtual vector<double> getParameters() const;
void saveToFile(string filename);
void readFromFile(string filename);
//@}
protected:
/** @name Accessors
*/
//@{
virtual void calculateWeights(BALL::Matrix<double>& dist, BALL::Vector<double>& w);
/** calculates weighted BALL::Matrix<double> X^T*X */
void calculateXX(BALL::Vector<double>& w, BALL::Matrix<double>& res);
/** calculates weighted BALL::Matrix<double> X^T*Y */
void calculateXY(BALL::Vector<double>& w, BALL::Matrix<double>& res);
/** calculates pairwise euclidean distance between all substances of m1 and m2 and saves them to BALL::Matrix<double> output */
void calculateEuclDistanceMatrix(BALL::Matrix<double>& m1, BALL::Matrix<double>& m2, BALL::Matrix<double>& output);
//@}
/** @name Attributes
*/
//@{
/** kernel width */
double kw_;
double lambda_;
//@}
};
}
}
#endif // ALLMODEL
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