| ▼Ndmlc | |
| ►Nserializer | |
| CHandler< xgboost::Entry > | |
| ▼Nrabit | |
| ►Nutils | |
| CPollHelper | Helper data structure to perform poll |
| ▼Nstd | |
| Chash< xgboost::IntrusivePtr< T > > | |
| ▼Nxgboost | Learner interface that integrates objective, gbm and evaluation together. This is the user facing XGBoost training module |
| ►Ncollective | |
| ►Ndetail | |
| CResultImpl | |
| CResult | An error type that's easier to handle than throwing dmlc exception. We can record and propagate the system error code |
| CSockAddrV6 | |
| CSockAddrV4 | |
| CSockAddress | Address for TCP socket, can be either IPv4 or IPv6 |
| CTCPSocket | TCP socket for simple communication |
| ►Ncommon | |
| ►Ndetail | |
| CSpanIterator | |
| CExtentValue | |
| CExtentAsBytesValue | |
| CIsAllowedExtentConversion | |
| CIsAllowedElementTypeConversion | |
| CIsSpanOracle | |
| CIsSpanOracle< Span< T, Extent > > | |
| CIsSpan | |
| CLess | |
| CGreater | |
| CSpan | Span class implementation, based on ISO++20 span<T>. The interface should be the same |
| CIterSpan | A simple custom Span type that uses general iterator instead of pointer |
| ►Ndetail | |
| CGradientPairInternal | Implementation of gradient statistics pair. Template specialisation may be used to overload different gradients types e.g. low precision, high precision, integer, floating point |
| ►Nlinalg | |
| ►Ndetail | |
| CArrayInterfaceHandler | |
| CAllTag | |
| CIntTag | |
| CRangeTag | |
| CConjunction | |
| CConjunction< B1 > | |
| CConjunction< B1, Bn... > | |
| CTensorView | A tensor view with static type and dimension. It implements indexing and slicing |
| CTensor | A tensor storage. To use it for other functionality like slicing one needs to obtain a view first. This way we can use it on both host and device |
| CGradientPairInt64 | Fixed point representation for high precision gradient pair. Has a different interface so we don't accidentally use it in gain calculations |
| ►CDMatrixCache | Thread-aware FIFO cache for DMatrix related data |
| CHash | |
| CItem | |
| CKey | |
| CDeviceSym | |
| CDeviceOrd | A type for device ordinal. The type is packed into 32-bit for efficient use in viewing types like linalg::TensorView |
| CContext | Runtime context for XGBoost. Contains information like threads and device |
| CTypedArrayRef | Used as a reference to a linalg::Matrix, or a vector |
| CMetaInfo | Meta information about dataset, always sit in memory |
| CEntry | Element from a sparse vector |
| CBatchParam | Parameters for constructing histogram index batches |
| CHostSparsePageView | |
| CSparsePage | In-memory storage unit of sparse batch, stored in CSR format |
| CCSCPage | |
| CExtSparsePage | Sparse page for exporting DMatrix. Same as SparsePage, just a different type to prevent being used internally |
| CSortedCSCPage | |
| CBatchIteratorImpl | |
| CBatchIterator | |
| CBatchSet | |
| CExtMemConfig | |
| CDMatrix | Internal data structured used by XGBoost to hold all external data |
| CFeatureMap | Feature map data structure to help text model dump. TODO(tqchen) consider make it even more lightweight |
| CGradientBooster | Interface of gradient boosting model |
| CGradientBoosterReg | Registry entry for tree updater |
| CGlobalConfiguration | |
| CInitNewThread | |
| CGradientContainer | Container for gradient produced by objective |
| CHostDeviceVectorImpl | |
| CHostDeviceVector | |
| CIntrusivePtrCell | 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 |
| ►CIntrusivePtr | 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 |
| CHash | |
| CValue | |
| CJsonString | |
| CJsonArray | |
| CJsonTypedArray | Typed array for Universal Binary JSON |
| CJsonObject | |
| CJsonNumber | |
| CJsonInteger | |
| CJsonNull | |
| CJsonBoolean | Describes both true and false |
| CJson | Data structure representing JSON format |
| ►CJsonReader | A json reader, currently error checking and utf-8 is not fully supported |
| CSourceLocation | |
| CJsonWriter | |
| CUBJReader | Reader for UBJSON https://ubjson.org/ |
| CUBJWriter | Writer for UBJSON https://ubjson.org/ |
| CLearner | 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 |
| CLearnerModelParam | Basic model parameters, used to describe the booster |
| CLinearUpdater | Interface of linear updater |
| CLinearUpdaterReg | Registry entry for linear updater |
| CMetric | Interface of evaluation metric used to evaluate model performance. This has nothing to do with training, but merely act as evaluation purpose |
| CMetricReg | 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" |
| CModel | |
| CConfigurable | |
| CMultiTargetTree | Tree structure for multi-target model |
| CObjFunction | The interface of objective function |
| CObjFunctionReg | Registry entry for objective factory functions |
| CXGBoostParameter | |
| CPredictionCacheEntry | Contains pointer to input matrix and associated cached predictions |
| CPredictionContainer | A container for managed prediction caches |
| CPredictor | 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 |
| CPredictorReg | Registry entry for predictor |
| CStringView | |
| CObjInfo | 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 |
| CTreeParam | Meta parameters of the tree |
| CRTreeNodeStat | Node statistics used in regression tree |
| ►CRegTree | Define regression tree to be the most common tree model |
| ►CCategoricalSplitMatrix | CSR-like matrix for categorical splits |
| CSegment | |
| CFVec | Dense feature vector that can be taken by RegTree and can be construct from sparse feature vector |
| CNode | Tree node |
| CTreeUpdater | Interface of tree update module, that performs update of a tree |
| CTreeUpdaterReg | Registry entry for tree updater |
| CXGBoostBatchCSR | Mini batch used in XGBoost Data Iteration |
