xgboost Namespace Reference

namespace of xgboost More...

Namespaces
	collective
	common
	detail
	gbm
	linalg
	system

Classes
class	GradientPairInt64
	Fixed point representation for high precision gradient pair. Has a different interface so we don't accidentally use it in gain calculations. More...
class	MetaInfo
	Meta information about dataset, always sit in memory. More...
struct	Entry
	Element from a sparse vector. More...
struct	BatchParam
	Parameters for constructing batches. More...
struct	HostSparsePageView
class	SparsePage
	In-memory storage unit of sparse batch, stored in CSR format. More...
class	CSCPage
class	ExtSparsePage
	Sparse page for exporting DMatrix. Same as SparsePage, just a different type to prevent being used internally. More...
class	SortedCSCPage
class	EllpackPage
	A page stored in ELLPACK format. More...
class	BatchIteratorImpl
class	BatchIterator
class	BatchSet
class	DMatrix
	Internal data structured used by XGBoost during training. More...
class	FeatureMap
	Feature map data structure to help text model dump. TODO(tqchen) consider make it even more lightweight. More...
class	GradientBooster
	interface of gradient boosting model. More...
struct	GradientBoosterReg
	Registry entry for tree updater. More...
struct	GenericParameter
struct	GlobalConfiguration
struct	HostDeviceVectorImpl
class	HostDeviceVector
class	IntrusivePtrCell
	Helper class for embedding reference counting into client objects. See https://www.boost.org/doc/libs/1_74_0/doc/html/atomic/usage_examples.html for discussions of memory order. More...
class	IntrusivePtr
	Implementation of Intrusive Pointer. A smart pointer that points to an object with an embedded reference counter. The underlying object must implement a friend function IntrusivePtrRefCount() that returns the ref counter (of type IntrusivePtrCell). The intrusive pointer is faster than std::shared_ptr<>: std::shared_ptr<> makes an extra memory allocation for the ref counter whereas the intrusive pointer does not. More...
class	Value
class	JsonString
class	JsonArray
class	JsonTypedArray
	Typed array for Universal Binary JSON. More...
class	JsonObject
class	JsonNumber
class	JsonInteger
class	JsonNull
class	JsonBoolean
	Describes both true and false. More...
class	Json
	Data structure representing JSON format. More...
class	JsonReader
class	JsonWriter
class	UBJReader
	Reader for UBJSON https://ubjson.org/. More...
class	UBJWriter
	Writer for UBJSON https://ubjson.org/. More...
struct	XGBAPIThreadLocalEntry
	entry to to easily hold returning information More...
class	Learner
	Learner class that does training and prediction. This is the user facing module of xgboost training. The Load/Save function corresponds to the model used in python/R. More...
struct	LearnerModelParam
class	LinearUpdater
	interface of linear updater More...
struct	LinearUpdaterReg
	Registry entry for linear updater. More...
class	Metric
	interface of evaluation metric used to evaluate model performance. This has nothing to do with training, but merely act as evaluation purpose. More...
struct	MetricReg
	Registry entry for Metric factory functions. The additional parameter const char* param gives the value after @, can be null. For example, metric map@3, then: param == "3". More...
struct	Model
struct	Configurable
class	ObjFunction
	interface of objective function More...
struct	ObjFunctionReg
	Registry entry for objective factory functions. More...
struct	XGBoostParameter
struct	PredictionCacheEntry
	Contains pointer to input matrix and associated cached predictions. More...
class	PredictionContainer
class	Predictor
	Performs prediction on individual training instances or batches of instances for GBTree. Prediction functions all take a GBTreeModel and a DMatrix as input and output a vector of predictions. The predictor does not modify any state of the model itself. More...
struct	PredictorReg
	Registry entry for predictor. More...
struct	StringView
struct	ObjInfo
	A struct returned by objective, which determines task at hand. The struct is not used by any algorithm yet, only for future development like categorical split. More...
struct	TreeParam
	meta parameters of the tree More...
struct	RTreeNodeStat
	node statistics used in regression tree More...
class	RegTree
	define regression tree to be the most common tree model. This is the data structure used in xgboost's major tree models. More...
class	TreeUpdater
	interface of tree update module, that performs update of a tree. More...
struct	TreeUpdaterReg
	Registry entry for tree updater. More...

Typedefs
using	bst_uint = uint32_t
	unsigned integer type used for feature index. More...
using	bst_int = int32_t
	integer type. More...
using	bst_ulong = uint64_t
	unsigned long integers More...
using	bst_float = float
	float type, used for storing statistics More...
using	bst_cat_t = int32_t
	Categorical value type. More...
using	bst_feature_t = uint32_t
	Type for data column (feature) index. More...
using	bst_bin_t = int32_t
	Type for histogram bin index. More...
using	bst_row_t = std::size_t
	Type for data row index. More...
using	bst_node_t = int32_t
	Type for tree node index. More...
using	bst_group_t = uint32_t
	Type for ranking group index. More...
using	GradientPair = detail::GradientPairInternal< float >
	gradient statistics pair usually needed in gradient boosting More...
using	GradientPairPrecise = detail::GradientPairInternal< double >
	High precision gradient statistics pair. More...
using	Args = std::vector< std::pair< std::string, std::string > >
using	omp_ulong = dmlc::omp_ulong
	define unsigned long for openmp loop More...
using	bst_omp_uint = dmlc::omp_uint
	define unsigned int for openmp loop More...
using	XGBoostVersionT = int32_t
	Type used for representing version number in binary form. More...
using	Context = GenericParameter
using	GlobalConfigThreadLocalStore = dmlc::ThreadLocalStore< GlobalConfiguration >
using	F32Array = JsonTypedArray< float, Value::ValueKind::kNumberArray >
	Typed UBJSON array for 32-bit floating point. More...
using	U8Array = JsonTypedArray< uint8_t, Value::ValueKind::kU8Array >
	Typed UBJSON array for uint8_t. More...
using	I32Array = JsonTypedArray< int32_t, Value::ValueKind::kI32Array >
	Typed UBJSON array for int32_t. More...
using	I64Array = JsonTypedArray< int64_t, Value::ValueKind::kI64Array >
	Typed UBJSON array for int64_t. More...
using	Object = JsonObject
using	Array = JsonArray
using	Number = JsonNumber
using	Integer = JsonInteger
using	Boolean = JsonBoolean
using	String = JsonString
using	Null = JsonNull

Enumerations
enum class	DataType : uint8_t {   kFloat32 = 1 , kDouble = 2 , kUInt32 = 3 , kUInt64 = 4 ,   kStr = 5 }
	data type accepted by xgboost interface More...
enum class	FeatureType : uint8_t { kNumerical = 0 , kCategorical = 1 }
enum	GPUAccess { kNone , kRead , kWrite }
	Controls data access from the GPU. More...
enum class	PredictionType : std::uint8_t {   kValue = 0 , kMargin = 1 , kContribution = 2 , kApproxContribution = 3 ,   kInteraction = 4 , kApproxInteraction = 5 , kLeaf = 6 }

Functions
template<typename T >
IntrusivePtrCell &	IntrusivePtrRefCount (T const *ptr) noexcept
	User defined function for returning embedded reference count. More...
template<class T , class U >
bool	operator== (IntrusivePtr< T > const &x, IntrusivePtr< U > const &y) noexcept
template<class T , class U >
bool	operator!= (IntrusivePtr< T > const &x, IntrusivePtr< U > const &y) noexcept
template<class T , class U >
bool	operator== (IntrusivePtr< T > const &x, U *y) noexcept
template<class T , class U >
bool	operator!= (IntrusivePtr< T > const &x, U *y) noexcept
template<class T , class U >
bool	operator== (T *x, IntrusivePtr< U > const &y) noexcept
template<class T , class U >
bool	operator!= (T *x, IntrusivePtr< U > const &y) noexcept
template<class T >
bool	operator< (IntrusivePtr< T > const &x, IntrusivePtr< T > const &y) noexcept
template<class T >
bool	operator<= (IntrusivePtr< T > const &x, IntrusivePtr< T > const &y) noexcept
template<class T >
bool	operator> (IntrusivePtr< T > const &x, IntrusivePtr< T > const &y) noexcept
template<class T >
bool	operator>= (IntrusivePtr< T > const &x, IntrusivePtr< T > const &y) noexcept
template<class E , class T , class Y >
std::basic_ostream< E, T > &	operator<< (std::basic_ostream< E, T > &os, IntrusivePtr< Y > const &p)
template<typename T >
bool	IsA (Value const *value)
template<typename T , typename U >
T *	Cast (U *value)
template<typename T >
bool	IsA (Json const &j)
	Check whether a Json object has specific type. More...
template<typename T , typename U >
auto	get (U &json) -> decltype(detail::GetImpl(*Cast< T >(&json.GetValue())))&
	Get Json value. More...
template<typename Parameter >
Object	ToJson (Parameter const &param)
template<typename Parameter >
Args	FromJson (Json const &obj, Parameter *param)
template<typename T >
T	BuiltinBSwap (T v)
template<typename T , std::enable_if_t< sizeof(T)==1 > * = nullptr>
T	ToBigEndian (T v)
std::ostream &	operator<< (std::ostream &os, StringView const v)
bool	operator== (StringView l, StringView r)
bool	operator!= (StringView l, StringView r)
bool	operator< (StringView l, StringView r)
bool	operator< (std::string const &l, StringView r)
bool	operator< (StringView l, std::string const &r)

Variables
constexpr bst_float	kRtEps = 1e-6f
	small eps gap for minimum split decision. More...

Detailed Description

namespace of xgboost

Copyright (c) by XGBoost Contributors 2019-2022

Copyright (c) by Contributors 2019-2022

Copyright 2021 by XGBoost Contributors

Copyright 2021-2022 by XGBoost Contributors

Typedef Documentation

Args

using xgboost::Args = typedef std::vector<std::pair<std::string, std::string> >

Array

using xgboost::Array = typedef JsonArray

Boolean

using xgboost::Boolean = typedef JsonBoolean

bst_bin_t

using xgboost::bst_bin_t = typedef int32_t

Type for histogram bin index.

bst_cat_t

using xgboost::bst_cat_t = typedef int32_t

Categorical value type.

bst_feature_t

using xgboost::bst_feature_t = typedef uint32_t

Type for data column (feature) index.

bst_float

using xgboost::bst_float = typedef float

float type, used for storing statistics

bst_group_t

using xgboost::bst_group_t = typedef uint32_t

Type for ranking group index.

bst_int

using xgboost::bst_int = typedef int32_t

integer type.

bst_node_t

using xgboost::bst_node_t = typedef int32_t

Type for tree node index.

bst_omp_uint

using xgboost::bst_omp_uint = typedef dmlc::omp_uint

define unsigned int for openmp loop

bst_row_t

using xgboost::bst_row_t = typedef std::size_t

Type for data row index.

Be careful ‘std::size_t’ is implementation-defined. Meaning that the binary representation of DMatrix might not be portable across platform. Booster model should be portable as parameters are floating points.

bst_uint

using xgboost::bst_uint = typedef uint32_t

unsigned integer type used for feature index.

bst_ulong

using xgboost::bst_ulong = typedef uint64_t

unsigned long integers

Context

using xgboost::Context = typedef GenericParameter

F32Array

using xgboost::F32Array = typedef JsonTypedArray<float, Value::ValueKind::kNumberArray>

Typed UBJSON array for 32-bit floating point.

GlobalConfigThreadLocalStore

using xgboost::GlobalConfigThreadLocalStore = typedef dmlc::ThreadLocalStore<GlobalConfiguration>

GradientPair

using xgboost::GradientPair = typedef detail::GradientPairInternal<float>

gradient statistics pair usually needed in gradient boosting

GradientPairPrecise

using xgboost::GradientPairPrecise = typedef detail::GradientPairInternal<double>

High precision gradient statistics pair.

I32Array

using xgboost::I32Array = typedef JsonTypedArray<int32_t, Value::ValueKind::kI32Array>

Typed UBJSON array for int32_t.

I64Array

using xgboost::I64Array = typedef JsonTypedArray<int64_t, Value::ValueKind::kI64Array>

Typed UBJSON array for int64_t.

Integer

using xgboost::Integer = typedef JsonInteger

Null

using xgboost::Null = typedef JsonNull

Number

using xgboost::Number = typedef JsonNumber

Object

using xgboost::Object = typedef JsonObject

omp_ulong

using xgboost::omp_ulong = typedef dmlc::omp_ulong

define unsigned long for openmp loop

String

using xgboost::String = typedef JsonString

U8Array

using xgboost::U8Array = typedef JsonTypedArray<uint8_t, Value::ValueKind::kU8Array>

Typed UBJSON array for uint8_t.

XGBoostVersionT

using xgboost::XGBoostVersionT = typedef int32_t

Type used for representing version number in binary form.

Enumeration Type Documentation

DataType

enum xgboost::DataType : uint8_t

strong

data type accepted by xgboost interface

Enumerator
kFloat32
kDouble
kUInt32
kUInt64
kStr

FeatureType

enum xgboost::FeatureType : uint8_t

strong

Enumerator
kNumerical
kCategorical

GPUAccess

enum xgboost::GPUAccess

Controls data access from the GPU.

Since a HostDeviceVector can have data on both the host and device, access control needs to be maintained to keep the data consistent.

There are 3 scenarios supported:

• Data is being manipulated on device. GPU has write access, host doesn't have access.
• Data is read-only on both the host and device.
• Data is being manipulated on the host. Host has write access, device doesn't have access.

Enumerator
kNone
kRead
kWrite

PredictionType

enum xgboost::PredictionType : std::uint8_t

strong

Enumerator
kValue
kMargin
kContribution
kApproxContribution
kInteraction
kApproxInteraction
kLeaf

Function Documentation

BuiltinBSwap()

template<typename T >

T xgboost::BuiltinBSwap

(

T

v

)

Cast()

template<typename T , typename U >

T* xgboost::Cast

(

U *

value

)

FromJson()

template<typename Parameter >

Args xgboost::FromJson	(	Json const &	obj,
		Parameter *	param
	)

get()

template<typename T , typename U >

auto xgboost::get

(

U &

json

)

-> decltype(detail::GetImpl(*Cast<T>(&json.GetValue())))&

Get Json value.

Template Parameters

T	One of the Json value type.

Parameters

json

Returns

Value contained in Json object of type T.

IntrusivePtrRefCount()

template<typename T >

IntrusivePtrCell& xgboost::IntrusivePtrRefCount ( T const *  ptr )

noexcept

User defined function for returning embedded reference count.

IsA() [1/2]

template<typename T >

bool xgboost::IsA

(

Json const &

j

)

Check whether a Json object has specific type.

Json json {Array{}};
bool is_array = IsA<Array>(json);
CHECK(is_array);

IsA() [2/2]

template<typename T >

bool xgboost::IsA

(

Value const *

value

)

operator!=() [1/4]

template<class T , class U >

bool xgboost::operator!= ( IntrusivePtr< T > const &  x, IntrusivePtr< U > const &  y  )

noexcept

operator!=() [2/4]

template<class T , class U >

bool xgboost::operator!= ( IntrusivePtr< T > const &  x, U *  y  )

noexcept

operator!=() [3/4]

bool xgboost::operator!= ( StringView  l, StringView  r  )

inline

operator!=() [4/4]

template<class T , class U >

bool xgboost::operator!= ( T *  x, IntrusivePtr< U > const &  y  )

noexcept

operator<() [1/4]

template<class T >

bool xgboost::operator< ( IntrusivePtr< T > const &  x, IntrusivePtr< T > const &  y  )

noexcept

operator<() [2/4]

bool xgboost::operator< ( std::string const &  l, StringView  r  )

inline

operator<() [3/4]

bool xgboost::operator< ( StringView  l, std::string const &  r  )

inline

operator<() [4/4]

bool xgboost::operator< ( StringView  l, StringView  r  )

inline

operator<<() [1/2]

template<class E , class T , class Y >

std::basic_ostream<E, T>& xgboost::operator<<	(	std::basic_ostream< E, T > &	os,
		IntrusivePtr< Y > const &	p
	)

operator<<() [2/2]

std::ostream& xgboost::operator<< ( std::ostream &  os, StringView const  v  )

inline

operator<=()

template<class T >

bool xgboost::operator<= ( IntrusivePtr< T > const &  x, IntrusivePtr< T > const &  y  )

noexcept

operator==() [1/4]

template<class T , class U >

bool xgboost::operator== ( IntrusivePtr< T > const &  x, IntrusivePtr< U > const &  y  )

noexcept

operator==() [2/4]

template<class T , class U >

bool xgboost::operator== ( IntrusivePtr< T > const &  x, U *  y  )

noexcept

operator==() [3/4]

bool xgboost::operator== ( StringView  l, StringView  r  )

inline

operator==() [4/4]

template<class T , class U >

bool xgboost::operator== ( T *  x, IntrusivePtr< U > const &  y  )

noexcept

operator>()

template<class T >

bool xgboost::operator> ( IntrusivePtr< T > const &  x, IntrusivePtr< T > const &  y  )

noexcept

operator>=()

template<class T >

bool xgboost::operator>= ( IntrusivePtr< T > const &  x, IntrusivePtr< T > const &  y  )

noexcept

ToBigEndian()

template<typename T , std::enable_if_t< sizeof(T)==1 > * = nullptr>

T xgboost::ToBigEndian ( T  v )

inline

ToJson()

template<typename Parameter >

Object xgboost::ToJson

(

Parameter const &

param

)

Variable Documentation

kRtEps

constexpr bst_float xgboost::kRtEps = 1e-6f

constexpr

small eps gap for minimum split decision.