/usr/include/BALL/QSAR/kernelModel.h is in libball1.4-dev 1.4.3~beta1-4.
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 | // -*- Mode: C++; tab-width: 2; -*-
// vi: set ts=2:
//
//
#ifndef KMODEL
#define KMODEL
#ifndef NLMODEL
#include <BALL/QSAR/nonlinearModel.h>
#endif
#ifndef LMODEL
#include <BALL/QSAR/linearModel.h>
#endif
#ifndef KERNEL
#include <BALL/QSAR/kernel.h>
#endif
namespace BALL
{
namespace QSAR
{
class BALL_EXPORT KernelModel : public NonLinearModel
{
public:
/** @name Constructors and Destructors
*/
//@{
KernelModel(const QSARData& q, int k_type, double p1, double p2);
KernelModel(const QSARData& q, String f, String g);
KernelModel(const QSARData& q, Eigen::VectorXd& w);
KernelModel(const QSARData& q, const LinearModel& lm, int column);
~KernelModel();
virtual void saveToFile(string filename);
virtual void readFromFile(string filename);
virtual Eigen::VectorXd predict(const vector<double>& substance, bool transform);
void operator=(const Model& m);
EIGEN_MAKE_ALIGNED_OPERATOR_NEW
//@}
/** @name Attributes
*/
//@{
Kernel* kernel;
//@}
protected:
/** @name Attributes
*/
//@{
/** Matrix containing the pairwise distances between all substances */
Eigen::MatrixXd K_;
/** resulting matrix with one column for each modeled activity and with one coefficient for each substance (i.e. one column for each column for Model.Y) */
//Matrix B;
//@}
/** @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
*/
//@{
void calculateOffsets();
void readKernelParametersFromFile(std::ifstream& in);
void saveKernelParametersToFile(std::ofstream& out);
void saveTrainingResult(std::ofstream& out);
void readTrainingResult(std::ifstream& input, int no_substances, int no_y);
friend class RegressionValidation;
//}@
};
}
}
#endif // NLMODEL
|