/usr/include/OTB-5.8/otbBoostMachineLearningModel.h is in libotb-dev 5.8.0+dfsg-3.
This file is owned by root:root, with mode 0o644.
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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 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 | /*=========================================================================
Program: ORFEO Toolbox
Language: C++
Date: $Date$
Version: $Revision$
Copyright (c) Centre National d'Etudes Spatiales. All rights reserved.
See OTBCopyright.txt for details.
This software is distributed WITHOUT ANY WARRANTY; without even
the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR
PURPOSE. See the above copyright notices for more information.
=========================================================================*/
#ifndef otbBoostMachineLearningModel_h
#define otbBoostMachineLearningModel_h
#include "otbRequiresOpenCVCheck.h"
#include "itkLightObject.h"
#include "itkFixedArray.h"
#include "otbMachineLearningModel.h"
class CvBoost;
namespace otb
{
template <class TInputValue, class TTargetValue>
class ITK_EXPORT BoostMachineLearningModel
: public MachineLearningModel <TInputValue, TTargetValue>
{
public:
/** Standard class typedefs. */
typedef BoostMachineLearningModel Self;
typedef MachineLearningModel<TInputValue, TTargetValue> Superclass;
typedef itk::SmartPointer<Self> Pointer;
typedef itk::SmartPointer<const Self> ConstPointer;
typedef typename Superclass::InputValueType InputValueType;
typedef typename Superclass::InputSampleType InputSampleType;
typedef typename Superclass::InputListSampleType InputListSampleType;
typedef typename Superclass::TargetValueType TargetValueType;
typedef typename Superclass::TargetSampleType TargetSampleType;
typedef typename Superclass::TargetListSampleType TargetListSampleType;
typedef typename Superclass::ConfidenceValueType ConfidenceValueType;
/** Run-time type information (and related methods). */
itkNewMacro(Self);
itkTypeMacro(BoostMachineLearningModel, MachineLearningModel);
/** Setters/Getters to the Boost type
* It can be CvBoost::DISCRETE, CvBoost::REAL, CvBoost::LOGIT, CvBoost::GENTLE
* Default is CvBoost::REAL.
* \see http://docs.opencv.org/modules/ml/doc/boosting.html#cvboostparams-cvboostparams
*/
itkGetMacro(BoostType, int);
itkSetMacro(BoostType, int);
/** Setters/Getters to the split criteria
* It can be CvBoost::DEFAULT, CvBoost::GINI, CvBoost::MISCLASS, CvBoost::SQERR
* Default is CvBoost::DEFAULT. It uses default value according to \c BoostType
* \see http://docs.opencv.org/modules/ml/doc/boosting.html#cvboost-predict
*/
itkGetMacro(SplitCrit, int);
itkSetMacro(SplitCrit, int);
/** Setters/Getters to the number of weak classifiers.
* Default is 100.
* \see http://docs.opencv.org/modules/ml/doc/boosting.html#cvboostparams-cvboostparams
*/
itkGetMacro(WeakCount, int);
itkSetMacro(WeakCount, int);
/** Setters/Getters to the threshold WeightTrimRate.
* A threshold between 0 and 1 used to save computational time.
* Samples with summary weight \f$ w \leq 1 - WeightTrimRate \f$ do not participate in the next iteration of training.
* Set this parameter to 0 to turn off this functionality.
* Default is 0.95
* \see http://docs.opencv.org/modules/ml/doc/boosting.html#cvboostparams-cvboostparams
*/
itkGetMacro(WeightTrimRate, double);
itkSetMacro(WeightTrimRate, double);
/** Setters/Getters to the maximum depth of the tree.
* Default is 1
* \see http://docs.opencv.org/modules/ml/doc/decision_trees.html#CvDTreeParams::CvDTreeParams%28%29
*/
itkGetMacro(MaxDepth, int);
itkSetMacro(MaxDepth, int);
/** Train the machine learning model */
void Train() ITK_OVERRIDE;
/** Save the model to file */
void Save(const std::string & filename, const std::string & name="") ITK_OVERRIDE;
/** Load the model from file */
void Load(const std::string & filename, const std::string & name="") ITK_OVERRIDE;
/**\name Classification model file compatibility tests */
//@{
/** Is the input model file readable and compatible with the corresponding classifier ? */
bool CanReadFile(const std::string &) ITK_OVERRIDE;
/** Is the input model file writable and compatible with the corresponding classifier ? */
bool CanWriteFile(const std::string &) ITK_OVERRIDE;
//@}
protected:
/** Constructor */
BoostMachineLearningModel();
/** Destructor */
~BoostMachineLearningModel() ITK_OVERRIDE;
/** Predict values using the model */
TargetSampleType DoPredict(const InputSampleType& input, ConfidenceValueType *quality=ITK_NULLPTR) const ITK_OVERRIDE;
/** PrintSelf method */
void PrintSelf(std::ostream& os, itk::Indent indent) const ITK_OVERRIDE;
private:
BoostMachineLearningModel(const Self &); //purposely not implemented
void operator =(const Self&); //purposely not implemented
CvBoost * m_BoostModel;
int m_BoostType;
int m_WeakCount;
double m_WeightTrimRate;
int m_SplitCrit;
int m_MaxDepth;
};
} // end namespace otb
#ifndef OTB_MANUAL_INSTANTIATION
#include "otbBoostMachineLearningModel.txx"
#endif
#endif
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