This class is a serializable Hoeffding tree model that can hold four different types of Hoeffding trees. More...

Public Types
typedef HoeffdingTree< GiniImpurity, BinaryDoubleNumericSplit, HoeffdingCategoricalSplit >	GiniBinaryTreeType
	Convenience typedef for GINI_BINARY tree type. More...

typedef HoeffdingTree< GiniImpurity, HoeffdingDoubleNumericSplit, HoeffdingCategoricalSplit >	GiniHoeffdingTreeType
	Convenience typedef for GINI_HOEFFDING tree type. More...

typedef HoeffdingTree< InformationGain, BinaryDoubleNumericSplit, HoeffdingCategoricalSplit >	InfoBinaryTreeType
	Convenience typedef for INFO_BINARY tree type. More...

typedef HoeffdingTree< InformationGain, HoeffdingDoubleNumericSplit, HoeffdingCategoricalSplit >	InfoHoeffdingTreeType
	Convenience typedef for INFO_HOEFFDING tree type. More...

enum	TreeType { GINI_HOEFFDING, GINI_BINARY, INFO_HOEFFDING, INFO_BINARY }
	This enumerates the four types of trees we can hold. More...

Public Member Functions
	HoeffdingTreeModel (const TreeType &type=GINI_HOEFFDING)
	Construct the Hoeffding tree model, but don't initialize any tree. More...

	HoeffdingTreeModel (const HoeffdingTreeModel &other)
	Copy the Hoeffding tree model from the given other model. More...

	HoeffdingTreeModel (HoeffdingTreeModel &&other)
	Move the Hoeffding tree model from the given other model. More...

	~HoeffdingTreeModel ()
	Clean up the given model. More...

void	BuildModel (const arma::mat &dataset, const data::DatasetInfo &datasetInfo, const arma::Row< size_t > &labels, const size_t numClasses, const bool batchTraining, const double successProbability, const size_t maxSamples, const size_t checkInterval, const size_t minSamples, const size_t bins, const size_t observationsBeforeBinning)
	Train the model on the given dataset with the given labels. More...

void	Classify (const arma::mat &dataset, arma::Row< size_t > &predictions) const
	Using the model, classify the given test points. More...

void	Classify (const arma::mat &dataset, arma::Row< size_t > &predictions, arma::rowvec &probabilities) const
	Using the model, classify the given test points, returning class probabilities. More...

size_t	NumNodes () const
	Get the number of nodes in the tree. More...

HoeffdingTreeModel &	operator= (const HoeffdingTreeModel &other)
	Copy the Hoeffding tree model from the given other model. More...

HoeffdingTreeModel &	operator= (HoeffdingTreeModel &&other)
	Move the Hoeffding tree model from the given other model. More...

template<typename Archive >
void	Serialize (Archive &ar, const unsigned int)
	Serialize the model. More...

void	Train (const arma::mat &dataset, const arma::Row< size_t > &labels, const bool batchTraining)
	Train in streaming mode on the given dataset. More...

Private Attributes
GiniBinaryTreeType *	giniBinaryTree
	This is used if we are using the Gini impurity and the binary numeric split. More...

GiniHoeffdingTreeType *	giniHoeffdingTree
	This is used if we are using the Gini impurity and the Hoeffding numeric split. More...

InfoBinaryTreeType *	infoBinaryTree
	This is used if we are using the information gain and the binary numeric split. More...

InfoHoeffdingTreeType *	infoHoeffdingTree
	This is used if we are using the information gain and the Hoeffding numeric split. More...

TreeType	type
	The type of tree we are using. More...

Detailed Description

This class is a serializable Hoeffding tree model that can hold four different types of Hoeffding trees.

It is meant to be used by the command-line program for Hoeffding trees.

Definition at line 22 of file hoeffding_tree_model.hpp.

Member Typedef Documentation

typedef HoeffdingTree<GiniImpurity, BinaryDoubleNumericSplit, HoeffdingCategoricalSplit> mlpack::tree::HoeffdingTreeModel::GiniBinaryTreeType

Convenience typedef for GINI_BINARY tree type.

Definition at line 39 of file hoeffding_tree_model.hpp.

typedef HoeffdingTree<GiniImpurity, HoeffdingDoubleNumericSplit, HoeffdingCategoricalSplit> mlpack::tree::HoeffdingTreeModel::GiniHoeffdingTreeType

Convenience typedef for GINI_HOEFFDING tree type.

Definition at line 36 of file hoeffding_tree_model.hpp.

typedef HoeffdingTree<InformationGain, BinaryDoubleNumericSplit, HoeffdingCategoricalSplit> mlpack::tree::HoeffdingTreeModel::InfoBinaryTreeType

Convenience typedef for INFO_BINARY tree type.

Definition at line 45 of file hoeffding_tree_model.hpp.

typedef HoeffdingTree<InformationGain, HoeffdingDoubleNumericSplit, HoeffdingCategoricalSplit> mlpack::tree::HoeffdingTreeModel::InfoHoeffdingTreeType

Convenience typedef for INFO_HOEFFDING tree type.

Definition at line 42 of file hoeffding_tree_model.hpp.

Member Enumeration Documentation

enum mlpack::tree::HoeffdingTreeModel::TreeType

This enumerates the four types of trees we can hold.

Enumerator
GINI_HOEFFDING
GINI_BINARY
INFO_HOEFFDING
INFO_BINARY

Definition at line 26 of file hoeffding_tree_model.hpp.

Constructor & Destructor Documentation

mlpack::tree::HoeffdingTreeModel::HoeffdingTreeModel ( const TreeType & type = GINI_HOEFFDING )

Construct the Hoeffding tree model, but don't initialize any tree.

Be sure to call Train() before doing anything with the model!

Parameters

type	Type of tree that will be used.

mlpack::tree::HoeffdingTreeModel::HoeffdingTreeModel ( const HoeffdingTreeModel & other )

Copy the Hoeffding tree model from the given other model.

Parameters

other Hoeffding tree model to copy.

mlpack::tree::HoeffdingTreeModel::HoeffdingTreeModel ( HoeffdingTreeModel && other )

Move the Hoeffding tree model from the given other model.

Parameters

other Hoeffding tree model to move.

mlpack::tree::HoeffdingTreeModel::~HoeffdingTreeModel ( )

Clean up the given model.

Member Function Documentation

void mlpack::tree::HoeffdingTreeModel::BuildModel	(	const arma::mat &	dataset,
		const data::DatasetInfo &	datasetInfo,
		const arma::Row< size_t > &	labels,
		const size_t	numClasses,
		const bool	batchTraining,
		const double	successProbability,
		const size_t	maxSamples,
		const size_t	checkInterval,
		const size_t	minSamples,
		const size_t	bins,
		const size_t	observationsBeforeBinning
	)

Train the model on the given dataset with the given labels.

This method just passes to the appropriate HoeffdingTree<...> constructor, and will train with one pass over the dataset.

Parameters

dataset	Dataset to train on.
datasetInfo	Information about dimensions of dataset.
labels	Labels for training set.
numClasses	Number of classes in dataset.
batchTraining	Whether or not to train in batch.
successProbability	Probability of success required in Hoeffding bound before a split can happen.
maxSamples	Maximum number of samples before a split is forced.
checkInterval	Number of samples required before each split check.
minSamples	If the node has seen this many points or fewer, no split will be allowed.
bins	Number of bins, for Hoeffding numeric split.
observationsBeforeBinning	Number of observations before binning, for Hoeffding numeric split.

void mlpack::tree::HoeffdingTreeModel::Classify	(	const arma::mat &	dataset,
		arma::Row< size_t > &	predictions
	)		const

Using the model, classify the given test points.

Be sure that BuildModel() has been called first!

Parameters

dataset	Dataset to classify.
predictions	Vector to store predictions for test points in.

void mlpack::tree::HoeffdingTreeModel::Classify	(	const arma::mat &	dataset,
		arma::Row< size_t > &	predictions,
		arma::rowvec &	probabilities
	)		const

Using the model, classify the given test points, returning class probabilities.

Parameters

dataset	Dataset to classify.
predictions	Vector to store predictions for test points in.
probabilities	Vector to store probabilities for test points in.

size_t mlpack::tree::HoeffdingTreeModel::NumNodes ( ) const

Get the number of nodes in the tree.

HoeffdingTreeModel& mlpack::tree::HoeffdingTreeModel::operator= ( const HoeffdingTreeModel & other )

Copy the Hoeffding tree model from the given other model.

Parameters

other Hoeffding tree model to copy.

HoeffdingTreeModel& mlpack::tree::HoeffdingTreeModel::operator= ( HoeffdingTreeModel && other )

Move the Hoeffding tree model from the given other model.

Parameters

other Hoeffding tree model to move.

template<typename Archive >

void mlpack::tree::HoeffdingTreeModel::Serialize	(	Archive &	ar,
		const unsigned	int
	)

inline

Serialize the model.

Definition at line 164 of file hoeffding_tree_model.hpp.

References mlpack::data::CreateNVP(), GINI_BINARY, GINI_HOEFFDING, giniBinaryTree, giniHoeffdingTree, INFO_BINARY, INFO_HOEFFDING, infoBinaryTree, infoHoeffdingTree, and type.

void mlpack::tree::HoeffdingTreeModel::Train	(	const arma::mat &	dataset,
		const arma::Row< size_t > &	labels,
		const bool	batchTraining
	)

Train in streaming mode on the given dataset.

This takes one pass. Be sure that BuildModel() has been called first!

Parameters

dataset	Dataset to train on.
labels	Labels for training set.
batchTraining	Whether or not to train in batch.

Member Data Documentation

GiniBinaryTreeType* mlpack::tree::HoeffdingTreeModel::giniBinaryTree

private

This is used if we are using the Gini impurity and the binary numeric split.

Definition at line 224 of file hoeffding_tree_model.hpp.

Referenced by Serialize().

GiniHoeffdingTreeType* mlpack::tree::HoeffdingTreeModel::giniHoeffdingTree

private

This is used if we are using the Gini impurity and the Hoeffding numeric split.

Definition at line 220 of file hoeffding_tree_model.hpp.

Referenced by Serialize().

InfoBinaryTreeType* mlpack::tree::HoeffdingTreeModel::infoBinaryTree

private

This is used if we are using the information gain and the binary numeric split.

Definition at line 232 of file hoeffding_tree_model.hpp.

Referenced by Serialize().

InfoHoeffdingTreeType* mlpack::tree::HoeffdingTreeModel::infoHoeffdingTree

private

This is used if we are using the information gain and the Hoeffding numeric split.

Definition at line 228 of file hoeffding_tree_model.hpp.

Referenced by Serialize().

TreeType mlpack::tree::HoeffdingTreeModel::type

private

The type of tree we are using.

Definition at line 216 of file hoeffding_tree_model.hpp.

Referenced by Serialize().

The documentation for this class was generated from the following file:

src/mlpack/methods/hoeffding_trees/hoeffding_tree_model.hpp

Public Types

Public Member Functions

Private Attributes

Detailed Description

Member Typedef Documentation

Member Enumeration Documentation

Constructor & Destructor Documentation

Member Function Documentation

Member Data Documentation