CLUS::BinaryProbabilisticDecisionTree< T_Splitter > Class Template Reference

#include <binaryprobabilisticdecisiontree.h>

Inheritance diagram for CLUS::BinaryProbabilisticDecisionTree< T_Splitter >:

[legend]Collaboration diagram for CLUS::BinaryProbabilisticDecisionTree< T_Splitter >:

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Public Member Functions
	BinaryProbabilisticDecisionTree (const Vector< int > &DDomainSize, int CsplitDim)
	~BinaryProbabilisticDecisionTree (void)
virtual int	InDim (void)
	Get the number of input dimensions.
virtual string	TypeName (void)
	Get the type of this object.
virtual void	Infer (void)
	Do the inference.
virtual void	Identify (void)
	Use the training data to learn a new structure.
virtual void	Prune (void)
	Prune the structure.
virtual int	SetOption (char *name, char *val)
	Set an option for the machine.
virtual void	SaveToStream (ostream &out)
	Output the structure data to a stream.
Protected Attributes
BinaryProbabilisticDecisionTreeNode< T_Splitter > *	root
const Vector< int > &	dDomainSize
	vector of discrete domain sizes
int	dsplitDim
	number of discrete split variables
int	csplitDim
	number of continuous split variables
double	minMass
	the minimum mass (sum of weights) to continue splitting
double	threshold
	the minimum value of the probability to belong to a partition to be considered
bool	bootstrapping
	do we do bootstrapping
int	bootstrappingRepetitions
	number of repetitions for bootstrapping

template<class T_Splitter>
class CLUS::BinaryProbabilisticDecisionTree< T_Splitter >

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Constructor & Destructor Documentation

template<class T_Splitter> CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::BinaryProbabilisticDecisionTree (  const Vector< int > &  DDomainSize, int  CsplitDim )  [inline]

Definition at line 75 of file binaryprobabilisticdecisiontree.h.

template<class T_Splitter> CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::~BinaryProbabilisticDecisionTree (  void   )  [inline]

Definition at line 88 of file binaryprobabilisticdecisiontree.h.

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Member Function Documentation

template<class T_Splitter> virtual void CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::Identify (  void   )  [inline, virtual]

Use the training data to learn a new structure. Reimplemented from CLUS::Machine. Definition at line 144 of file binaryprobabilisticdecisiontree.h.

template<class T_Splitter> virtual int CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::InDim (  void   )  [inline, virtual]

Get the number of input dimensions. Reimplemented from CLUS::Machine. Definition at line 94 of file binaryprobabilisticdecisiontree.h.

template<class T_Splitter> virtual void CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::Infer (  void   )  [inline, virtual]

Do the inference. Reimplemented from CLUS::Machine. Definition at line 104 of file binaryprobabilisticdecisiontree.h.

template<class T_Splitter> virtual void CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::Prune (  void   )  [inline, virtual]

Prune the structure. Reimplemented from CLUS::Machine. Definition at line 171 of file binaryprobabilisticdecisiontree.h.

template<class T_Splitter> virtual void CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::SaveToStream (  ostream &  out  )  [inline, virtual]

Output the structure data to a stream. Parameters: out  stream for output Reimplemented from CLUS::Machine. Definition at line 205 of file binaryprobabilisticdecisiontree.h.

template<class T_Splitter> virtual int CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::SetOption (  char *  name, char *  val )  [inline, virtual]

Set an option for the machine. Parameters: name  name of option to be set val  value of option Reimplemented from CLUS::Machine. Definition at line 193 of file binaryprobabilisticdecisiontree.h.

template<class T_Splitter> virtual string CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::TypeName (  void   )  [inline, virtual]

Get the type of this object. Returns: name of object type as a string Reimplemented from CLUS::Machine. Definition at line 99 of file binaryprobabilisticdecisiontree.h. Referenced by CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::SaveToStream().

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Field Documentation

template<class T_Splitter> bool CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::bootstrapping [protected]

do we do bootstrapping Definition at line 69 of file binaryprobabilisticdecisiontree.h. Referenced by CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::BinaryProbabilisticDecisionTree().

template<class T_Splitter> int CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::bootstrappingRepetitions [protected]

number of repetitions for bootstrapping Definition at line 72 of file binaryprobabilisticdecisiontree.h. Referenced by CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::BinaryProbabilisticDecisionTree().

template<class T_Splitter> int CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::csplitDim [protected]

number of continuous split variables Definition at line 60 of file binaryprobabilisticdecisiontree.h. Referenced by CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::BinaryProbabilisticDecisionTree(), CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::Identify(), CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::InDim(), CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::Infer(), and CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::SaveToStream().

template<class T_Splitter> const Vector<int>& CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::dDomainSize [protected]

vector of discrete domain sizes Definition at line 54 of file binaryprobabilisticdecisiontree.h. Referenced by CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::BinaryProbabilisticDecisionTree(), CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::Identify(), and CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::SaveToStream().

template<class T_Splitter> int CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::dsplitDim [protected]

number of discrete split variables Definition at line 57 of file binaryprobabilisticdecisiontree.h. Referenced by CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::BinaryProbabilisticDecisionTree(), CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::Identify(), CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::InDim(), CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::Infer(), CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::Prune(), and CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::SaveToStream().

template<class T_Splitter> double CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::minMass [protected]

the minimum mass (sum of weights) to continue splitting Definition at line 63 of file binaryprobabilisticdecisiontree.h. Referenced by CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::BinaryProbabilisticDecisionTree(), CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::Identify(), and CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::SetOption().

template<class T_Splitter> BinaryProbabilisticDecisionTreeNode< T_Splitter >* CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::root [protected]

Definition at line 51 of file binaryprobabilisticdecisiontree.h. Referenced by CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::BinaryProbabilisticDecisionTree(), CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::Identify(), CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::Infer(), CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::Prune(), CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::SaveToStream(), and CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::~BinaryProbabilisticDecisionTree().

template<class T_Splitter> double CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::threshold [protected]

the minimum value of the probability to belong to a partition to be considered Definition at line 66 of file binaryprobabilisticdecisiontree.h. Referenced by CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::BinaryProbabilisticDecisionTree(), CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::Identify(), CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::Infer(), CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::Prune(), and CLUS::BinaryProbabilisticDecisionTree< T_Splitter >::SetOption().

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

• binaryprobabilisticdecisiontree.h

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