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| FernTrainer () |
| Constructor.
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virtual | ~FernTrainer () |
| Destructor.
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void | setFeatureHandler (pcl::FeatureHandler< FeatureType, DataSet, ExampleIndex > &feature_handler) |
| Sets the feature handler used to create and evaluate features.
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void | setStatsEstimator (pcl::StatsEstimator< LabelType, NodeType, DataSet, ExampleIndex > &stats_estimator) |
| Sets the object for estimating the statistics for tree nodes.
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void | setFernDepth (const std::size_t fern_depth) |
| Sets the maximum depth of the learned tree.
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void | setNumOfFeatures (const std::size_t num_of_features) |
| Sets the number of features used to find optimal decision features.
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void | setNumOfThresholds (const std::size_t num_of_threshold) |
| Sets the number of thresholds tested for finding the optimal decision threshold on the feature responses.
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void | setTrainingDataSet (DataSet &data_set) |
| Sets the input data set used for training.
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void | setExamples (std::vector< ExampleIndex > &examples) |
| Example indices that specify the data used for training.
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void | setLabelData (std::vector< LabelType > &label_data) |
| Sets the label data corresponding to the example data.
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void | train (Fern< FeatureType, NodeType > &fern) |
| Trains a decision tree using the set training data and settings.
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template<class FeatureType, class DataSet, class LabelType, class ExampleIndex, class NodeType>
class pcl::FernTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >
Trainer for a Fern.
Definition at line 55 of file fern_trainer.h.
template<class FeatureType , class DataSet , class LabelType , class ExampleIndex , class NodeType >
void pcl::FernTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >::createThresholdsUniform |
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const std::size_t |
num_of_thresholds, |
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std::vector< float > & |
values, |
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std::vector< float > & |
thresholds |
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staticprotected |
Creates uniformely distrebuted thresholds over the range of the supplied values.
- Parameters
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[in] | num_of_thresholds | the number of thresholds to create |
[in] | values | the values for estimating the expected value range |
[out] | thresholds | the resulting thresholds |
Definition at line 299 of file fern_trainer.hpp.
template<class FeatureType , class DataSet , class LabelType , class ExampleIndex , class NodeType >
void pcl::FernTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >::setExamples |
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std::vector< ExampleIndex > & |
examples | ) |
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inline |
Example indices that specify the data used for training.
- Parameters
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Definition at line 132 of file fern_trainer.h.
template<class FeatureType , class DataSet , class LabelType , class ExampleIndex , class NodeType >
void pcl::FernTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >::setFernDepth |
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const std::size_t |
fern_depth | ) |
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inline |
Sets the maximum depth of the learned tree.
- Parameters
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[in] | fern_depth | maximum depth of the learned tree |
Definition at line 91 of file fern_trainer.h.
template<class FeatureType , class DataSet , class LabelType , class ExampleIndex , class NodeType >
void pcl::FernTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >::setLabelData |
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std::vector< LabelType > & |
label_data | ) |
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inline |
Sets the label data corresponding to the example data.
- Parameters
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[in] | label_data | the label data |
Definition at line 142 of file fern_trainer.h.
template<class FeatureType , class DataSet , class LabelType , class ExampleIndex , class NodeType >
void pcl::FernTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >::setNumOfFeatures |
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const std::size_t |
num_of_features | ) |
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inline |
Sets the number of features used to find optimal decision features.
- Parameters
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[in] | num_of_features | the number of features |
Definition at line 101 of file fern_trainer.h.
template<class FeatureType , class DataSet , class LabelType , class ExampleIndex , class NodeType >
void pcl::FernTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >::setNumOfThresholds |
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const std::size_t |
num_of_threshold | ) |
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inline |
Sets the number of thresholds tested for finding the optimal decision threshold on the feature responses.
- Parameters
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[in] | num_of_threshold | the number of thresholds |
Definition at line 112 of file fern_trainer.h.
template<class FeatureType , class DataSet , class LabelType , class ExampleIndex , class NodeType >
void pcl::FernTrainer< FeatureType, DataSet, LabelType, ExampleIndex, NodeType >::train |
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pcl::Fern< FeatureType, NodeType > & |
fern | ) |
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