Point Cloud Library (PCL)  1.11.1-dev
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