Logo
OpenCV  2.4.13
Open Source Computer Vision
Public Types | Public Member Functions | Protected Member Functions | Protected Attributes | List of all members
CvGBTrees Class Reference

#include <ml.hpp>

Inheritance diagram for CvGBTrees:

Public Types

enum   { SQUARED_LOSS =0, ABSOLUTE_LOSS, HUBER_LOSS =3, DEVIANCE_LOSS }
 

Public Member Functions

  CvGBTrees ()
 
  CvGBTrees (const CvMat *trainData, int tflag, const CvMat *responses, const CvMat *varIdx=0, const CvMat *sampleIdx=0, const CvMat *varType=0, const CvMat *missingDataMask=0, CvGBTreesParams params=CvGBTreesParams())
 
virtual  ~CvGBTrees ()
 
virtual bool  train (const CvMat *trainData, int tflag, const CvMat *responses, const CvMat *varIdx=0, const CvMat *sampleIdx=0, const CvMat *varType=0, const CvMat *missingDataMask=0, CvGBTreesParams params=CvGBTreesParams(), bool update=false)
 
virtual bool  train (CvMLData *data, CvGBTreesParams params=CvGBTreesParams(), bool update=false)
 
virtual float  predict_serial (const CvMat *sample, const CvMat *missing=0, CvMat *weakResponses=0, CvSlice slice=CV_WHOLE_SEQ, int k=-1) const
 
virtual float  predict (const CvMat *sample, const CvMat *missing=0, CvMat *weakResponses=0, CvSlice slice=CV_WHOLE_SEQ, int k=-1) const
 
virtual void  clear ()
 
virtual float  calc_error (CvMLData *_data, int type, std::vector< float > *resp=0)
 
virtual void  write (CvFileStorage *fs, const char *name) const
 
virtual void  read (CvFileStorage *fs, CvFileNode *node)
 
  CvGBTrees (const cv::Mat &trainData, int tflag, const cv::Mat &responses, const cv::Mat &varIdx=cv::Mat(), const cv::Mat &sampleIdx=cv::Mat(), const cv::Mat &varType=cv::Mat(), const cv::Mat &missingDataMask=cv::Mat(), CvGBTreesParams params=CvGBTreesParams())
 
virtual bool  train (const cv::Mat &trainData, int tflag, const cv::Mat &responses, const cv::Mat &varIdx=cv::Mat(), const cv::Mat &sampleIdx=cv::Mat(), const cv::Mat &varType=cv::Mat(), const cv::Mat &missingDataMask=cv::Mat(), CvGBTreesParams params=CvGBTreesParams(), bool update=false)
 
virtual float  predict (const cv::Mat &sample, const cv::Mat &missing=cv::Mat(), const cv::Range &slice=cv::Range::all(), int k=-1) const
 
- Public Member Functions inherited from CvStatModel
  CvStatModel ()
 
virtual  ~CvStatModel ()
 
virtual void  save (const char *filename, const char *name=0) const
 
virtual void  load (const char *filename, const char *name=0)
 

Protected Member Functions

virtual void  find_gradient (const int k=0)
 
virtual void  change_values (CvDTree *tree, const int k=0)
 
virtual float  find_optimal_value (const CvMat *_Idx)
 
virtual void  do_subsample ()
 
void  leaves_get (CvDTreeNode **leaves, int &count, CvDTreeNode *node)
 
CvDTreeNode **  GetLeaves (const CvDTree *dtree, int &len)
 
virtual bool  problem_type () const
 
virtual void  write_params (CvFileStorage *fs) const
 
virtual void  read_params (CvFileStorage *fs, CvFileNode *fnode)
 
int  get_len (const CvMat *mat) const
 

Protected Attributes

CvDTreeTrainData *  data
 
CvGBTreesParams  params
 
CvSeq **  weak
 
CvMat *  orig_response
 
CvMat *  sum_response
 
CvMat *  sum_response_tmp
 
CvMat *  sample_idx
 
CvMat *  subsample_train
 
CvMat *  subsample_test
 
CvMat *  missing
 
CvMat *  class_labels
 
cv::RNG *  rng
 
int  class_count
 
float  delta
 
float  base_value
 
- Protected Attributes inherited from CvStatModel
const char *  default_model_name
 

Member Enumeration Documentation

anonymous enum
Enumerator
SQUARED_LOSS 
ABSOLUTE_LOSS 
HUBER_LOSS 
DEVIANCE_LOSS 

Constructor & Destructor Documentation

CvGBTrees::CvGBTrees ( )
CvGBTrees::CvGBTrees ( const CvMat *  trainData,
int  tflag,
const CvMat *  responses,
const CvMat *  varIdx = 0,
const CvMat *  sampleIdx = 0,
const CvMat *  varType = 0,
const CvMat *  missingDataMask = 0,
CvGBTreesParams  params = CvGBTreesParams() 
)
virtual CvGBTrees::~CvGBTrees ( )
virtual
CvGBTrees::CvGBTrees ( const cv::Mat &  trainData,
int  tflag,
const cv::Mat &  responses,
const cv::Mat &  varIdx = cv::Mat(),
const cv::Mat &  sampleIdx = cv::Mat(),
const cv::Mat &  varType = cv::Mat(),
const cv::Mat &  missingDataMask = cv::Mat(),
CvGBTreesParams  params = CvGBTreesParams() 
)

Member Function Documentation

virtual float CvGBTrees::calc_error ( CvMLData *  _data,
int  type,
std::vector< float > *  resp = 0 
)
virtual
virtual void CvGBTrees::change_values ( CvDTree *  tree,
const int  k = 0 
)
protectedvirtual
virtual void CvGBTrees::clear ( )
virtual

Reimplemented from CvStatModel.

virtual void CvGBTrees::do_subsample ( )
protectedvirtual
virtual void CvGBTrees::find_gradient ( const int  k = 0 )
protectedvirtual
virtual float CvGBTrees::find_optimal_value ( const CvMat *  _Idx )
protectedvirtual
int CvGBTrees::get_len ( const CvMat *  mat ) const
protected
CvDTreeNode** CvGBTrees::GetLeaves ( const CvDTree *  dtree,
int &  len 
)
protected
void CvGBTrees::leaves_get ( CvDTreeNode **  leaves,
int &  count,
CvDTreeNode *  node 
)
protected
virtual float CvGBTrees::predict ( const CvMat *  sample,
const CvMat *  missing = 0,
CvMat *  weakResponses = 0,
CvSlice  slice = CV_WHOLE_SEQ ,
int  k = -1 
) const
virtual
virtual float CvGBTrees::predict ( const cv::Mat &  sample,
const cv::Mat &  missing = cv::Mat(),
const cv::Range &  slice = cv::Range::all(),
int  k = -1 
) const
virtual
virtual float CvGBTrees::predict_serial ( const CvMat *  sample,
const CvMat *  missing = 0,
CvMat *  weakResponses = 0,
CvSlice  slice = CV_WHOLE_SEQ ,
int  k = -1 
) const
virtual
virtual bool CvGBTrees::problem_type ( ) const
protectedvirtual
virtual void CvGBTrees::read ( CvFileStorage *  fs,
CvFileNode *  node 
)
virtual

Reimplemented from CvStatModel.

virtual void CvGBTrees::read_params ( CvFileStorage *  fs,
CvFileNode *  fnode 
)
protectedvirtual
virtual bool CvGBTrees::train ( const CvMat *  trainData,
int  tflag,
const CvMat *  responses,
const CvMat *  varIdx = 0,
const CvMat *  sampleIdx = 0,
const CvMat *  varType = 0,
const CvMat *  missingDataMask = 0,
CvGBTreesParams  params = CvGBTreesParams(),
bool  update = false 
)
virtual
virtual bool CvGBTrees::train ( CvMLData *  data,
CvGBTreesParams  params = CvGBTreesParams(),
bool  update = false 
)
virtual
virtual bool CvGBTrees::train ( const cv::Mat &  trainData,
int  tflag,
const cv::Mat &  responses,
const cv::Mat &  varIdx = cv::Mat(),
const cv::Mat &  sampleIdx = cv::Mat(),
const cv::Mat &  varType = cv::Mat(),
const cv::Mat &  missingDataMask = cv::Mat(),
CvGBTreesParams  params = CvGBTreesParams(),
bool  update = false 
)
virtual
virtual void CvGBTrees::write ( CvFileStorage *  fs,
const char *  name 
) const
virtual

Reimplemented from CvStatModel.

virtual void CvGBTrees::write_params ( CvFileStorage *  fs ) const
protectedvirtual

Member Data Documentation

float CvGBTrees::base_value
protected
int CvGBTrees::class_count
protected
CvMat* CvGBTrees::class_labels
protected
CvDTreeTrainData* CvGBTrees::data
protected
float CvGBTrees::delta
protected
CvMat* CvGBTrees::missing
protected
CvMat* CvGBTrees::orig_response
protected
CvGBTreesParams CvGBTrees::params
protected
cv::RNG* CvGBTrees::rng
protected
CvMat* CvGBTrees::sample_idx
protected
CvMat* CvGBTrees::subsample_test
protected
CvMat* CvGBTrees::subsample_train
protected
CvMat* CvGBTrees::sum_response
protected
CvMat* CvGBTrees::sum_response_tmp
protected
CvSeq** CvGBTrees::weak
protected
The documentation for this class was generated from the following file:

AltStyle によって変換されたページ (->オリジナル) /