pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType > Member List

This is the complete list of members for pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >, including all inherited members.

createThresholdsUniform(const std::size_t num_of_thresholds, std::vector< float > &values, std::vector< float > &thresholds)	pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >	protectedstatic
DecisionTreeTrainer()	pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >
setDecisionTreeDataProvider(typename pcl::DecisionTreeTrainerDataProvider< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >::Ptr &dtdp)	pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >	inline
setExamples(std::vector< ExampleIndex > &examples)	pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >	inline
setFeatureHandler(pcl::FeatureHandler< FeatureType, DataSet, ExampleIndex > &feature_handler)	pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >	inline
setLabelData(std::vector< LabelType > &label_data)	pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >	inline
setMaxTreeDepth(const std::size_t max_tree_depth)	pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >	inline
setMinExamplesForSplit(std::size_t n)	pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >	inline
setNumOfFeatures(const std::size_t num_of_features)	pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >	inline
setNumOfThresholds(const std::size_t num_of_threshold)	pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >	inline
setRandomFeaturesAtSplitNode(bool b)	pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >	inline
setStatsEstimator(pcl::StatsEstimator< LabelType, NodeType, DataSet, ExampleIndex > &stats_estimator)	pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >	inline
setThresholds(std::vector< float > &thres)	pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >	inline
setTrainingDataSet(DataSet &data_set)	pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >	inline
train(DecisionTree< NodeType > &tree)	pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >
trainDecisionTreeNode(std::vector< FeatureType > &features, std::vector< ExampleIndex > &examples, std::vector< LabelType > &label_data, std::size_t max_depth, NodeType &node)	pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >	protected
~DecisionTreeTrainer()	pcl::DecisionTreeTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >	virtual