This is the complete list of members for CvGBTrees, including all inherited members.
| ABSOLUTE_LOSS enum value | CvGBTrees | |
| base_value | CvGBTrees | protected |
| calc_error(CvMLData *_data, int type, std::vector< float > *resp=0) | CvGBTrees | virtual |
| change_values(CvDTree *tree, const int k=0) | CvGBTrees | protectedvirtual |
| class_count | CvGBTrees | protected |
| class_labels | CvGBTrees | protected |
| clear() | CvGBTrees | virtual |
| 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()) | 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()) | CvGBTrees | |
| CvStatModel() | CvStatModel | |
| data | CvGBTrees | protected |
| default_model_name | CvStatModel | protected |
| delta | CvGBTrees | protected |
| DEVIANCE_LOSS enum value | CvGBTrees | |
| do_subsample() | CvGBTrees | protectedvirtual |
| find_gradient(const int k=0) | CvGBTrees | protectedvirtual |
| find_optimal_value(const CvMat *_Idx) | CvGBTrees | protectedvirtual |
| get_len(const CvMat *mat) const | CvGBTrees | protected |
| GetLeaves(const CvDTree *dtree, int &len) | CvGBTrees | protected |
| HUBER_LOSS enum value | CvGBTrees | |
| leaves_get(CvDTreeNode **leaves, int &count, CvDTreeNode *node) | CvGBTrees | protected |
| load(const char *filename, const char *name=0) | CvStatModel | virtual |
| missing | CvGBTrees | protected |
| orig_response | CvGBTrees | protected |
| params | CvGBTrees | protected |
| predict(const CvMat *sample, const CvMat *missing=0, CvMat *weakResponses=0, CvSlice slice=CV_WHOLE_SEQ, int k=-1) const | CvGBTrees | virtual |
| predict(const cv::Mat &sample, const cv::Mat &missing=cv::Mat(), const cv::Range &slice=cv::Range::all(), int k=-1) const | CvGBTrees | virtual |
| predict_serial(const CvMat *sample, const CvMat *missing=0, CvMat *weakResponses=0, CvSlice slice=CV_WHOLE_SEQ, int k=-1) const | CvGBTrees | virtual |
| problem_type() const | CvGBTrees | protectedvirtual |
| read(CvFileStorage *fs, CvFileNode *node) | CvGBTrees | virtual |
| read_params(CvFileStorage *fs, CvFileNode *fnode) | CvGBTrees | protectedvirtual |
| rng | CvGBTrees | protected |
| sample_idx | CvGBTrees | protected |
| save(const char *filename, const char *name=0) const | CvStatModel | virtual |
| SQUARED_LOSS enum value | CvGBTrees | |
| subsample_test | CvGBTrees | protected |
| subsample_train | CvGBTrees | protected |
| sum_response | CvGBTrees | protected |
| sum_response_tmp | CvGBTrees | protected |
| 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) | CvGBTrees | virtual |
| train(CvMLData *data, CvGBTreesParams params=CvGBTreesParams(), bool update=false) | CvGBTrees | virtual |
| 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) | CvGBTrees | virtual |
| weak | CvGBTrees | protected |
| write(CvFileStorage *fs, const char *name) const | CvGBTrees | virtual |
| write_params(CvFileStorage *fs) const | CvGBTrees | protectedvirtual |
| ~CvGBTrees() | CvGBTrees | virtual |
| ~CvStatModel() | CvStatModel | virtual |