mlpack::tree::BestBinaryNumericSplit< FitnessFunction > Class Template Reference

The BestBinaryNumericSplit is a splitting function for decision trees that will exhaustively search a numeric dimension for the best binary split. More...

Classes
class	AuxiliarySplitInfo

Static Public Member Functions
template<typename ElemType >
static size_t	CalculateDirection (const ElemType &point, const arma::Col< ElemType > &classProbabilities, const AuxiliarySplitInfo< ElemType > &)
	Given a point, calculate which child it should go to (left or right). More...
template<typename ElemType >
static size_t	NumChildren (const arma::Col< ElemType > &, const AuxiliarySplitInfo< ElemType > &)
	Returns 2, since the binary split always has two children. More...
template<typename VecType >
static double	SplitIfBetter (const double bestGain, const VecType &data, const arma::Row< size_t > &labels, const size_t numClasses, const size_t minimumLeafSize, arma::Col< typename VecType::elem_type > &classProbabilities, AuxiliarySplitInfo< typename VecType::elem_type > &aux)
	Check if we can split a node. More...

Detailed Description

template<typename FitnessFunction>
class mlpack::tree::BestBinaryNumericSplit< FitnessFunction >

The BestBinaryNumericSplit is a splitting function for decision trees that will exhaustively search a numeric dimension for the best binary split.

Template Parameters

FitnessFunction

Fitness function to use to calculate gain.

Definition at line 22 of file best_binary_numeric_split.hpp.

Member Function Documentation

template<typename FitnessFunction >

template<typename ElemType >

static size_t mlpack::tree::BestBinaryNumericSplit< FitnessFunction >::CalculateDirection ( const ElemType &  point, const arma::Col< ElemType > &  classProbabilities, const AuxiliarySplitInfo< ElemType > &    )

static

Given a point, calculate which child it should go to (left or right).

Parameters

point	Point to calculate direction of.
classProbabilities	Auxiliary information for the split.
aux	(Unused) auxiliary information for the split.

Referenced by mlpack::tree::BestBinaryNumericSplit< FitnessFunction >::NumChildren().

template<typename FitnessFunction >

template<typename ElemType >

static size_t mlpack::tree::BestBinaryNumericSplit< FitnessFunction >::NumChildren ( const arma::Col< ElemType > &  , const AuxiliarySplitInfo< ElemType > &    )

inlinestatic

Returns 2, since the binary split always has two children.

Definition at line 62 of file best_binary_numeric_split.hpp.

References mlpack::tree::BestBinaryNumericSplit< FitnessFunction >::CalculateDirection().

template<typename FitnessFunction >

template<typename VecType >

static double mlpack::tree::BestBinaryNumericSplit< FitnessFunction >::SplitIfBetter ( const double  bestGain, const VecType &  data, const arma::Row< size_t > &  labels, const size_t  numClasses, const size_t  minimumLeafSize, arma::Col< typename VecType::elem_type > &  classProbabilities, AuxiliarySplitInfo< typename VecType::elem_type > &  aux  )

static

Check if we can split a node.

If we can split a node in a way that improves on 'bestGain', then we return the improved gain. Otherwise we return the value 'bestGain'. If a split is made, then classProbabilities and aux may be modified.

Parameters

bestGain	Best gain seen so far (we'll only split if we find gain better than this).
data	The dimension of data points to check for a split in.
numCategories	Number of categories in the categorical data.
labels	Labels for each point.
numClasses	Number of classes in the dataset.
minimumLeafSize	Minimum number of points in a leaf node for splitting.
classProbabilities	Class probabilities vector, which may be filled with split information a successful split.
aux	Auxiliary split information, which may be modified on a successful split.

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

• src/mlpack/methods/decision_tree/best_binary_numeric_split.hpp