| ▼Ndmlc | |
| ►Nserializer | |
| CHandler< xgboost::Entry > | |
| ▼Nxgboost | Namespace of xgboost |
| ►Ncommon | |
| ►Ndetail | |
| CExtentAsBytesValue | |
| CExtentValue | |
| CGreater | |
| CIsAllowedElementTypeConversion | |
| CIsAllowedExtentConversion | |
| CIsSpan | |
| CIsSpanOracle | |
| CIsSpanOracle< Span< T, Extent > > | |
| CLess | |
| CSpanIterator | |
| CAFTLoss | The AFT loss function |
| CAFTParam | Parameter structure for AFT loss and metric |
| CBase64InStream | Stream that reads from base64, note we take from file pointers |
| CBase64OutStream | Stream that write to base64, note we take from file pointers |
| CBlockedSpace2d | |
| CColumn | Column storage, to be used with ApplySplit. Note that each bin id is stored as index[i] + index_base. Different types of column index for each column allow to reduce the memory usage |
| CColumnMatrix | Collection of columns, with support for construction from GHistIndexMatrix |
| CColumnSampler | Handles selection of columns due to colsample_bytree, colsample_bylevel and colsample_bynode parameters. Should be initialised before tree construction and to reset when tree construction is completed |
| CCompressedBufferWriter | Writes bit compressed symbols to a memory buffer. Use CompressedIterator to read symbols back from buffer. Currently limited to a maximum symbol size of 28 bits |
| CCompressedIterator | Read symbols from a bit compressed memory buffer. Usable on device and host |
| CConfigParser | Implementation of config reader |
| CCutsBuilder | |
| CDenseColumn | |
| CDenseCuts | Cut configuration for dense dataset |
| CExtremeDist | The extreme distribution, also known as the Gumbel (minimum) distribution |
| CFixedSizeStream | A simple class used to consume `dmlc::Stream' all at once |
| CGHistBuilder | Builder for histograms of gradient statistics |
| CGHistIndexBlock | |
| CGHistIndexBlockMatrix | |
| CGHistIndexMatrix | Preprocessed global index matrix, in CSR format |
| CGKQuantileSketch | Quantile sketch use WQSummary |
| ►CGKSummary | Traditional GK summary |
| CEntry | Entry in the sketch summary |
| CQueue | Input data queue before entering the summary |
| CHistCollection | Histogram of gradient statistics for multiple nodes |
| CHistogramCuts | |
| CIndex | |
| CLogisticDist | The (standard) logistic distribution |
| CMonitor | Timing utility used to measure total method execution time over the lifetime of the containing object |
| CNormalDist | The (standard) normal distribution |
| CParallelGHistBuilder | Stores temporary histograms to compute them in parallel Supports processing multiple tree-nodes for nested parallelism Able to reduce histograms across threads in efficient way |
| CParallelGroupBuilder | Multi-thread version of group builder |
| ►CPartitionBuilder | |
| CBlockInfo | |
| CPeekableInStream | Input stream that support additional PeekRead operation, besides read |
| CProbabilityDistribution | Interface for a probability distribution |
| ►CQuantileSketchTemplate | Template for all quantile sketch algorithm that uses merge/prune scheme |
| CSummaryContainer | Same as summary, but use STL to backup the space |
| ►CRange | |
| CIterator | |
| CRange1d | |
| ►CRowSetCollection | Collection of rowset |
| CElem | Data structure to store an instance set, a subset of rows (instances) associated with a particular node in a decision tree |
| CSplit | |
| CSpan | Span class implementation, based on ISO++20 span<T>. The interface should be the same |
| CSparseColumn | |
| CSparseCuts | Cut configuration for sparse dataset |
| CStreamBufferReader | Buffer reader of the stream that allows you to get |
| CTimer | |
| CTransform | Do Transformation on HostDeviceVectors |
| ►CWQSummary | Experimental wsummary |
| CEntry | Entry in the sketch summary |
| ►CQueue | Input data queue before entering the summary |
| CQEntry | |
| CWQuantileSketch | Quantile sketch use WQSummary |
| CWXQSummary | Try to do efficient pruning |
| CWXQuantileSketch | Quantile sketch use WXQSummary |
| ►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 |
| CBatchIterator | |
| CBatchIteratorImpl | |
| CBatchParam | Parameters for constructing batches |
| CBatchSet | |
| ►CBitFieldContainer | A non-owning type with auxiliary methods defined for manipulating bits |
| CPos | |
| CConfigurable | |
| CCSCPage | |
| CDataSource | 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 |
| CDMatrix | Internal data structured used by XGBoost during training. There are two ways to create a customized DMatrix that reads in user defined-format |
| CEllpackPage | A page stored in ELLPACK format |
| CEntry | Element from a sparse vector |
| CFeatureMap | Feature map data structure to help text model dump. TODO(tqchen) consider make it even more lightweight |
| CFixedPrecisionStreamContainer | |
| CGenericParameter | |
| CGradientBooster | Interface of gradient boosting model |
| CGradientBoosterReg | Registry entry for tree updater |
| CHostDeviceVector | |
| CHostDeviceVectorImpl | |
| CJson | Data structure representing JSON format |
| CJsonArray | |
| CJsonBoolean | Describes both true and false |
| CJsonInteger | |
| CJsonNull | |
| CJsonNumber | |
| CJsonObject | |
| ►CJsonReader | |
| CSourceLocation | |
| CJsonString | |
| CJsonWriter | |
| CLBitsPolicy | |
| 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 | |
| CLinearUpdater | Interface of linear updater |
| CLinearUpdaterReg | Registry entry for linear updater |
| CMetaInfo | Meta information about dataset, always sit in memory |
| 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 | |
| CObjFunction | Interface of objective function |
| CObjFunctionReg | Registry entry for objective factory functions |
| CPredictionCacheEntry | Contains pointer to input matrix and associated cached predictions |
| CPredictionContainer | |
| 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 |
| CRBitsPolicy | |
| ►CRegTree | Define regression tree to be the most common tree model. This is the data structure used in xgboost's major tree models |
| CFVec | Dense feature vector that can be taken by RegTree and can be construct from sparse feature vector |
| CNode | Tree node |
| CRTreeNodeStat | Node statistics used in regression tree |
| CSortedCSCPage | |
| CSparsePage | In-memory storage unit of sparse batch, stored in CSR format |
| CStringView | |
| CTrainingObserver | |
| CTreeParam | Meta parameters of the tree |
| CTreeUpdater | Interface of tree update module, that performs update of a tree |
| CTreeUpdaterReg | Registry entry for tree updater |
| CValue | |
| CVersion | |
| CXGBAPIThreadLocalEntry | Entry to to easily hold returning information |
| CXGBoostParameter | |
| CXGBoostBatchCSR | Mini batch used in XGBoost Data Iteration |
