xgboost Namespace Reference

namespace of xgboost More...

Namespaces
	common
	detail

Classes
struct	AllVisibleImpl
class	BatchIterator
class	BatchIteratorImpl
class	BatchSet
class	DataSource
	This is data structure that user can pass to DMatrix::Create to create a DMatrix for training, user can create this data structure for customized Data Loading on single machine. More...
class	DMatrix
	Internal data structured used by XGBoost during training. There are two ways to create a customized DMatrix that reads in user defined-format. More...
struct	Entry
	Element from a sparse vector. More...
class	FeatureMap
	Feature map data structure to help text model dump. TODO(tqchen) consider make it even more lightweight. More...
class	GPUDistribution
class	GPUSet
class	GradientBooster
	interface of gradient boosting model. More...
struct	GradientBoosterReg
	Registry entry for tree updater. More...
class	HostDeviceVector
struct	HostDeviceVectorImpl
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...
class	LinearUpdater
	interface of linear updater More...
struct	LinearUpdaterReg
	Registry entry for linear updater. More...
class	MetaInfo
	Meta information about dataset, always sit in memory. 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...
class	ObjFunction
	interface of objective function More...
struct	ObjFunctionReg
	Registry entry for objective factory functions. More...
class	Predictor
	Performs prediction on individual training instances or batches of instances for GBTree. The predictor also manages a prediction cache associated with input matrices. If possible, it will use previously calculated predictions instead of calculating new predictions. 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...
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	RowSet
	A vector-like structure to represent set of rows. But saves the memory when all rows are in the set (common case in xgb) More...
struct	RTreeNodeStat
	node statistics used in regression tree More...
class	SparsePage
	In-memory storage unit of sparse batch, stored in CSR format. More...
struct	TreeParam
	meta parameters of the tree 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 in boost, used for feature index and row index. More...
using	bst_int = int32_t
typedef uint64_t	bst_ulong
	long integers More...
using	bst_float = float
	float type, used for storing statistics 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	GradientPairInteger = detail::GradientPairInternal< int64_t >
	High precision gradient statistics pair with integer backed storage. Operators are associative where floating point versions are not associative. More...
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...

Enumerations
enum	DataType { kFloat32 = 1, kDouble = 2, kUInt32 = 3, kUInt64 = 4 }
	data type accepted by xgboost interface More...
enum	GPUAccess { kNone, kRead, kWrite }

Functions
GPUAccess	operator- (GPUAccess a, GPUAccess b)

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

Detailed Description

namespace of xgboost

Copyright by Contributors 2017

Copyright 2018 XGBoost contributors

Typedef Documentation

bst_float

using xgboost::bst_float = typedef float

float type, used for storing statistics

bst_int

using xgboost::bst_int = typedef int32_t

bst_omp_uint

using xgboost::bst_omp_uint = typedef dmlc::omp_uint

define unsigned int for openmp loop

bst_uint

using xgboost::bst_uint = typedef uint32_t

unsigned integer type used in boost, used for feature index and row index.

bst_ulong

typedef uint64_t xgboost::bst_ulong

long integers

GradientPair

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

gradient statistics pair usually needed in gradient boosting

GradientPairInteger

using xgboost::GradientPairInteger = typedef detail::GradientPairInternal<int64_t>

High precision gradient statistics pair with integer backed storage. Operators are associative where floating point versions are not associative.

GradientPairPrecise

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

High precision gradient statistics pair.

omp_ulong

using xgboost::omp_ulong = typedef dmlc::omp_ulong

define unsigned long for openmp loop

Enumeration Type Documentation

DataType

enum xgboost::DataType

data type accepted by xgboost interface

Enumerator
kFloat32
kDouble
kUInt32
kUInt64

GPUAccess

enum xgboost::GPUAccess

Enumerator
kNone
kRead
kWrite

Function Documentation

operator-()

GPUAccess xgboost::operator- ( GPUAccess  a, GPUAccess  b  )

inline

Variable Documentation

kRtEps

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

small eps gap for minimum split decision.