xgboost::tree::SplitEntryContainer< GradientT > Struct Template Reference

statistics that is helpful to store and represent a split solution for the tree More...

#include <param.h>

Public Member Functions
void	CopyAndCollect (SplitEntryContainer< GradientT > const &that, std::vector< uint32_t > *collected_cat_bits, std::vector< std::size_t > *cat_bits_sizes)
	Copy primitive fields into this, and collect cat_bits into a vector.
template<typename G >
void	CopyAndCollect (SplitEntryContainer< GradientT > const &that, std::vector< uint32_t > *collected_cat_bits, std::vector< std::size_t > *cat_bits_sizes, std::vector< G > *collected_gradients)
	Copy primitive fields into this, and collect cat_bits and gradient sums into vectors.
bst_feature_t	SplitIndex () const
bool	DefaultLeft () const
bool	NeedReplace (bst_float new_loss_chg, unsigned split_index) const
	decides whether we can replace current entry with the given statistics
bool	Update (const SplitEntryContainer &e)
	update the split entry, replace it if e is better
template<typename GradientSumT >
bool	Update (bst_float new_loss_chg, bst_feature_t split_index, float new_split_value, bool default_left, bool is_cat, GradientSumT const &left_sum, GradientSumT const &right_sum)
	update the split entry, replace it if e is better

Static Public Member Functions
static void	Reduce (SplitEntryContainer &dst, const SplitEntryContainer &src)
	same as update, used by AllReduce

Data Fields
bst_float	loss_chg {0.0f}
	loss change after split this node
bst_feature_t	sindex {0}
	split index
bst_float	split_value {0.0f}
std::vector< uint32_t >	cat_bits
bool	is_cat {false}
GradientT	left_sum
GradientT	right_sum

Friends
std::ostream &	operator<< (std::ostream &os, SplitEntryContainer const &s)

Detailed Description

template<typename GradientT>
struct xgboost::tree::SplitEntryContainer< GradientT >

statistics that is helpful to store and represent a split solution for the tree

Member Function Documentation

CopyAndCollect() [1/2]

template<typename GradientT >

void xgboost::tree::SplitEntryContainer< GradientT >::CopyAndCollect ( SplitEntryContainer< GradientT > const &  that, std::vector< uint32_t > *  collected_cat_bits, std::vector< std::size_t > *  cat_bits_sizes  )

inline

Copy primitive fields into this, and collect cat_bits into a vector.

This is used for allgather.

Parameters

that	The other entry to copy from
collected_cat_bits	The vector to collect cat_bits
cat_bits_sizes	The sizes of the collected cat_bits

CopyAndCollect() [2/2]

template<typename GradientT >

template<typename G >

void xgboost::tree::SplitEntryContainer< GradientT >::CopyAndCollect ( SplitEntryContainer< GradientT > const &  that, std::vector< uint32_t > *  collected_cat_bits, std::vector< std::size_t > *  cat_bits_sizes, std::vector< G > *  collected_gradients  )

inline

Copy primitive fields into this, and collect cat_bits and gradient sums into vectors.

This is used for allgather.

Parameters

that	The other entry to copy from
collected_cat_bits	The vector to collect cat_bits
cat_bits_sizes	The sizes of the collected cat_bits
collected_gradients	The vector to collect gradients

DefaultLeft()

template<typename GradientT >

bool xgboost::tree::SplitEntryContainer< GradientT >::DefaultLeft ( ) const

inline

Returns

whether missing value goes to left branch

NeedReplace()

template<typename GradientT >

bool xgboost::tree::SplitEntryContainer< GradientT >::NeedReplace ( bst_float  new_loss_chg, unsigned  split_index  ) const

inline

decides whether we can replace current entry with the given statistics

This function gives better priority to lower index when loss_chg == new_loss_chg. Not the best way, but helps to give consistent result during multi-thread execution.

Parameters

new_loss_chg	the loss reduction get through the split
split_index	the feature index where the split is on

SplitIndex()

template<typename GradientT >

bst_feature_t xgboost::tree::SplitEntryContainer< GradientT >::SplitIndex ( ) const

inline

Returns

feature index to split on

Update() [1/2]

template<typename GradientT >

template<typename GradientSumT >

bool xgboost::tree::SplitEntryContainer< GradientT >::Update ( bst_float  new_loss_chg, bst_feature_t  split_index, float  new_split_value, bool  default_left, bool  is_cat, GradientSumT const &  left_sum, GradientSumT const &  right_sum  )

inline

update the split entry, replace it if e is better

Parameters

new_loss_chg	loss reduction of new candidate
split_index	feature index to split on
new_split_value	the split point
default_left	whether the missing value goes to left

Returns

whether the proposed split is better and can replace current split

Update() [2/2]

template<typename GradientT >

bool xgboost::tree::SplitEntryContainer< GradientT >::Update ( const SplitEntryContainer< GradientT > &  e )

inline

update the split entry, replace it if e is better

Parameters

e	candidate split solution

Returns

whether the proposed split is better and can replace current split

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

• External/xgboost/src/tree/param.h