xgboost
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namespace of xgboost More...
Namespaces | |
common | |
detail | |
gbm | |
Classes | |
class | BatchIterator |
class | BatchIteratorImpl |
struct | BatchParam |
Parameters for constructing batches. More... | |
class | BatchSet |
struct | BitFieldContainer |
A non-owning type with auxiliary methods defined for manipulating bits. More... | |
struct | Configurable |
class | CSCPage |
class | DMatrix |
Internal data structured used by XGBoost during training. More... | |
class | EllpackPage |
A page stored in ELLPACK 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... | |
struct | from_chars_result |
struct | GenericParameter |
class | GradientBooster |
interface of gradient boosting model. More... | |
struct | GradientBoosterReg |
Registry entry for tree updater. More... | |
class | HostDeviceVector |
struct | HostDeviceVectorImpl |
struct | HostSparsePageView |
class | Json |
Data structure representing JSON format. More... | |
class | JsonArray |
class | JsonBoolean |
Describes both true and false. More... | |
class | JsonInteger |
class | JsonNull |
class | JsonNumber |
class | JsonObject |
class | JsonReader |
class | JsonString |
class | JsonWriter |
struct | LBitsPolicy |
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 | 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... | |
struct | Model |
struct | NumericLimits |
struct | NumericLimits< float > |
struct | NumericLimits< int64_t > |
class | ObjFunction |
interface of objective function More... | |
struct | ObjFunctionReg |
Registry entry for objective factory functions. More... | |
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 | RBitsPolicy |
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... | |
struct | RTreeNodeStat |
node statistics used in regression tree More... | |
class | SortedCSCPage |
class | SparsePage |
In-memory storage unit of sparse batch, stored in CSR format. More... | |
struct | StringView |
struct | to_chars_result |
class | TrainingObserver |
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... | |
class | Value |
struct | Version |
struct | XGBAPIThreadLocalEntry |
entry to to easily hold returning information More... | |
struct | XGBoostParameter |
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_feature_t = uint32_t |
Type for data column (feature) 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 | Object = JsonObject |
using | Array = JsonArray |
using | Number = JsonNumber |
using | Integer = JsonInteger |
using | Boolean = JsonBoolean |
using | String = JsonString |
using | Null = JsonNull |
using | LBitField64 = BitFieldContainer< uint64_t, LBitsPolicy< uint64_t > > |
using | RBitField8 = BitFieldContainer< uint8_t, RBitsPolicy< unsigned char > > |
Enumerations | |
enum | DataType : uint8_t { DataType::kFloat32 = 1, DataType::kDouble = 2, DataType::kUInt32 = 3, DataType::kUInt64 = 4, DataType::kStr = 5 } |
data type accepted by xgboost interface More... | |
enum | FeatureType : uint8_t { FeatureType::kNumerical } |
enum | GPUAccess { kNone, kRead, kWrite } |
Controls data access from the GPU. More... | |
Functions | |
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) |
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 ¶m) |
template<typename Parameter > | |
void | FromJson (Json const &obj, Parameter *param) |
to_chars_result | to_chars (char *first, char *last, float value) |
to_chars_result | to_chars (char *first, char *last, int64_t value) |
from_chars_result | from_chars (const char *buffer, const char *end, float &value) |
Variables | |
constexpr bst_float | kRtEps = 1e-6f |
small eps gap for minimum split decision. More... | |
namespace of xgboost
Implement std::to_chars
and std::from_chars
for float. Only base 10 with scientific format is supported. The implementation guarantees roundtrip reproducibility.
Copyright (c) by XGBoost Contributors 2019-2020
Copyright (c) by Contributors 2019
Copyright 2019 by XGBoost Contributors
Copyright by Contributors 2017-2019
Copyright 2018 XGBoost contributors
Copyright 2019 XGBoost contributors
using xgboost::Args = typedef std::vector<std::pair<std::string, std::string> > |
using xgboost::Array = typedef JsonArray |
using xgboost::Boolean = typedef JsonBoolean |
using xgboost::bst_feature_t = typedef uint32_t |
Type for data column (feature) index.
using xgboost::bst_float = typedef float |
float type, used for storing statistics
using xgboost::bst_group_t = typedef uint32_t |
Type for ranking group index.
using xgboost::bst_int = typedef int32_t |
integer type.
using xgboost::bst_node_t = typedef int32_t |
Type for tree node index.
using xgboost::bst_omp_uint = typedef dmlc::omp_uint |
define unsigned int for openmp loop
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.
using xgboost::bst_uint = typedef uint32_t |
unsigned integer type used for feature index.
using xgboost::bst_ulong = typedef uint64_t |
unsigned long integers
using xgboost::GradientPair = typedef detail::GradientPairInternal<float> |
gradient statistics pair usually needed in gradient boosting
using xgboost::GradientPairPrecise = typedef detail::GradientPairInternal<double> |
High precision gradient statistics pair.
using xgboost::Integer = typedef JsonInteger |
using xgboost::LBitField64 = typedef BitFieldContainer<uint64_t, LBitsPolicy<uint64_t> > |
using xgboost::Null = typedef JsonNull |
using xgboost::Number = typedef JsonNumber |
using xgboost::Object = typedef JsonObject |
using xgboost::omp_ulong = typedef dmlc::omp_ulong |
define unsigned long for openmp loop
using xgboost::RBitField8 = typedef BitFieldContainer<uint8_t, RBitsPolicy<unsigned char> > |
using xgboost::String = typedef JsonString |
using xgboost::XGBoostVersionT = typedef int32_t |
Type used for representing version number in binary form.
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strong |
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strong |
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:
Enumerator | |
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kNone | |
kRead | |
kWrite |
T* xgboost::Cast | ( | U * | value | ) |
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inline |
void xgboost::FromJson | ( | Json const & | obj, |
Parameter * | param | ||
) |
auto xgboost::get | ( | U & | json | ) | -> decltype(detail::GetImpl(*Cast<T>(&json.GetValue())))& |
bool xgboost::IsA | ( | Value const * | value | ) |
bool xgboost::IsA | ( | Json const | j | ) |
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inline |
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inline |
Object xgboost::ToJson | ( | Parameter const & | param | ) |
constexpr bst_float xgboost::kRtEps = 1e-6f |
small eps gap for minimum split decision.