#include <ml.hpp>
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| CvRTrees () |
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virtual | ~CvRTrees () |
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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, CvRTParams params=CvRTParams()) |
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virtual bool | train (CvMLData *data, CvRTParams params=CvRTParams()) |
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virtual float | predict (const CvMat *sample, const CvMat *missing=0) const |
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virtual float | predict_prob (const CvMat *sample, const CvMat *missing=0) const |
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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(), CvRTParams params=CvRTParams()) |
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virtual float | predict (const cv::Mat &sample, const cv::Mat &missing=cv::Mat()) const |
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virtual float | predict_prob (const cv::Mat &sample, const cv::Mat &missing=cv::Mat()) const |
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virtual cv::Mat | getVarImportance () |
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virtual void | clear () |
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virtual const CvMat * | get_var_importance () |
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virtual float | get_proximity (const CvMat *sample1, const CvMat *sample2, const CvMat *missing1=0, const CvMat *missing2=0) const |
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virtual float | calc_error (CvMLData *data, int type, std::vector< float > *resp=0) |
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virtual float | get_train_error () |
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virtual void | read (CvFileStorage *fs, CvFileNode *node) |
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virtual void | write (CvFileStorage *fs, const char *name) const |
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CvMat * | get_active_var_mask () |
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CvRNG * | get_rng () |
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int | get_tree_count () const |
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CvForestTree * | get_tree (int i) const |
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| CvStatModel () |
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virtual | ~CvStatModel () |
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virtual void | save (const char *filename, const char *name=0) const |
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virtual void | load (const char *filename, const char *name=0) |
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§ CvRTrees()
§ ~CvRTrees()
virtual CvRTrees::~CvRTrees |
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§ calc_error()
virtual float CvRTrees::calc_error |
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CvMLData * |
data, |
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int |
type, |
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std::vector< float > * |
resp = 0 |
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§ clear()
virtual void CvRTrees::clear |
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§ get_active_var_mask()
CvMat* CvRTrees::get_active_var_mask |
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§ get_proximity()
virtual float CvRTrees::get_proximity |
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const CvMat * |
sample1, |
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const CvMat * |
sample2, |
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const CvMat * |
missing1 = 0 , |
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const CvMat * |
missing2 = 0 |
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§ get_rng()
CvRNG* CvRTrees::get_rng |
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§ get_train_error()
virtual float CvRTrees::get_train_error |
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§ get_tree()
§ get_tree_count()
int CvRTrees::get_tree_count |
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§ get_var_importance()
virtual const CvMat* CvRTrees::get_var_importance |
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§ getName()
virtual std::string CvRTrees::getName |
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const |
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§ getVarImportance()
virtual cv::Mat CvRTrees::getVarImportance |
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§ grow_forest()
§ predict() [1/2]
virtual float CvRTrees::predict |
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const CvMat * |
sample, |
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const CvMat * |
missing = 0 |
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§ predict() [2/2]
§ predict_prob() [1/2]
virtual float CvRTrees::predict_prob |
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const CvMat * |
sample, |
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const CvMat * |
missing = 0 |
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§ predict_prob() [2/2]
virtual float CvRTrees::predict_prob |
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const cv::Mat & |
sample, |
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const cv::Mat & |
missing = cv::Mat() |
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§ read()
§ train() [1/3]
§ train() [2/3]
§ train() [3/3]
§ write()
§ active_var_mask
CvMat* CvRTrees::active_var_mask |
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§ data
§ nclasses
§ nsamples
§ ntrees
§ oob_error
double CvRTrees::oob_error |
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§ rng
§ trees
§ var_importance
CvMat* CvRTrees::var_importance |
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The documentation for this class was generated from the following file: