CvDTree Member List

This is the complete list of members for CvDTree, including all inherited members.
calc_error(CvMLData *trainData, int type, std::vector< float > *resp=0)CvDTree [virtual]
calc_node_dir(CvDTreeNode *node)CvDTree [protected, virtual]
calc_node_value(CvDTreeNode *node)CvDTree [protected, virtual]
clear()CvDTree [virtual]
cluster_categories(const int *vectors, int vector_count, int var_count, int *sums, int k, int *cluster_labels)CvDTree [protected, virtual]
complete_node_dir(CvDTreeNode *node)CvDTree [protected, virtual]
cut_tree(int T, int fold, double min_alpha)CvDTree [protected, virtual]
cv::DTreeBestSplitFinderCvDTree [friend]
CvDTree()CvDTree
CvStatModel()CvStatModel
dataCvDTree [protected]
default_model_nameCvStatModel [protected]
do_train(const CvMat *_subsample_idx)CvDTree [protected, virtual]
find_best_split(CvDTreeNode *n)CvDTree [protected, virtual]
find_split_cat_class(CvDTreeNode *n, int vi, float init_quality=0, CvDTreeSplit *_split=0, uchar *ext_buf=0)CvDTree [protected, virtual]
find_split_cat_reg(CvDTreeNode *n, int vi, float init_quality=0, CvDTreeSplit *_split=0, uchar *ext_buf=0)CvDTree [protected, virtual]
find_split_ord_class(CvDTreeNode *n, int vi, float init_quality=0, CvDTreeSplit *_split=0, uchar *ext_buf=0)CvDTree [protected, virtual]
find_split_ord_reg(CvDTreeNode *n, int vi, float init_quality=0, CvDTreeSplit *_split=0, uchar *ext_buf=0)CvDTree [protected, virtual]
find_surrogate_split_cat(CvDTreeNode *n, int vi, uchar *ext_buf=0)CvDTree [protected, virtual]
find_surrogate_split_ord(CvDTreeNode *n, int vi, uchar *ext_buf=0)CvDTree [protected, virtual]
free_prune_data(bool cut_tree)CvDTree [protected, virtual]
free_tree()CvDTree [protected, virtual]
get_data()CvDTree
get_pruned_tree_idx() const CvDTree
get_root() const CvDTree
get_var_importance()CvDTree [virtual]
getVarImportance()CvDTree [virtual]
load(const char *filename, const char *name=0)CvStatModel [virtual]
predict(const CvMat *sample, const CvMat *missingDataMask=0, bool preprocessedInput=false) const CvDTree [virtual]
predict(const cv::Mat &sample, const cv::Mat &missingDataMask=cv::Mat(), bool preprocessedInput=false) const CvDTree [virtual]
prune_cv()CvDTree [protected, virtual]
pruned_tree_idxCvDTree
read(CvFileStorage *fs, CvFileNode *node)CvDTree [virtual]
read(CvFileStorage *fs, CvFileNode *node, CvDTreeTrainData *data)CvDTree [virtual]
read_node(CvFileStorage *fs, CvFileNode *node, CvDTreeNode *parent)CvDTree [protected, virtual]
read_split(CvFileStorage *fs, CvFileNode *node)CvDTree [protected, virtual]
read_tree_nodes(CvFileStorage *fs, CvFileNode *node)CvDTree [protected, virtual]
rootCvDTree [protected]
save(const char *filename, const char *name=0) const CvStatModel [virtual]
split_node_data(CvDTreeNode *n)CvDTree [protected, virtual]
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, CvDTreeParams params=CvDTreeParams())CvDTree [virtual]
train(CvMLData *trainData, CvDTreeParams params=CvDTreeParams())CvDTree [virtual]
train(CvDTreeTrainData *trainData, const CvMat *subsampleIdx)CvDTree [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(), CvDTreeParams params=CvDTreeParams())CvDTree [virtual]
try_split_node(CvDTreeNode *n)CvDTree [protected, virtual]
update_tree_rnc(int T, int fold)CvDTree [protected, virtual]
var_importanceCvDTree [protected]
write(CvFileStorage *fs, const char *name) const CvDTree [virtual]
write(CvFileStorage *fs) const CvDTree [virtual]
write_node(CvFileStorage *fs, CvDTreeNode *node) const CvDTree [protected, virtual]
write_split(CvFileStorage *fs, CvDTreeSplit *split) const CvDTree [protected, virtual]
write_tree_nodes(CvFileStorage *fs) const CvDTree [protected, virtual]
~CvDTree()CvDTree [virtual]
~CvStatModel()CvStatModel [virtual]
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