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 |