xgboost

Class Hierarchy

Go to the graphical class hierarchy

This inheritance list is sorted roughly, but not completely, alphabetically:
[detail level 1 2 3]

C xgboost::common::AFTLoss< Distribution > | The AFT loss function
C xgboost::BatchIterator< T > |
C xgboost::BatchIteratorImpl< T > |
C xgboost::BatchParam | Parameters for constructing batches
C xgboost::BatchSet< T > |
C xgboost::BitFieldContainer< VT, Direction, IsConst > | A non-owning type with auxiliary methods defined for manipulating bits
►C xgboost::BitFieldContainer< VT, LBitsPolicy< VT, false >, false > |
C xgboost::LBitsPolicy< VT, IsConst > |
►C xgboost::BitFieldContainer< VT, RBitsPolicy< VT > > |
C xgboost::RBitsPolicy< VT > |
C xgboost::common::BlockedSpace2d |
C xgboost::common::PartitionBuilder< BlockSize >::BlockInfo |
►C xgboost::common::Column< BinIdxType > | 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
C xgboost::common::DenseColumn< BinIdxType > |
C xgboost::common::SparseColumn< BinIdxType > |
C xgboost::common::ColumnMatrix | Collection of columns, with support for construction from GHistIndexMatrix
C xgboost::common::ColumnSampler | 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
C xgboost::common::CompressedBufferWriter | 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
C xgboost::common::CompressedIterator< T > | Read symbols from a bit compressed memory buffer. Usable on device and host
C xgboost::common::ConfigParser | Implementation of config reader
►C xgboost::Configurable |
C xgboost::GradientBooster | Interface of gradient boosting model
C xgboost::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
C xgboost::LinearUpdater | Interface of linear updater
C xgboost::Metric | Interface of evaluation metric used to evaluate model performance. This has nothing to do with training, but merely act as evaluation purpose
C xgboost::ObjFunction | Interface of objective function
C xgboost::TreeUpdater | Interface of tree update module, that performs update of a tree
C xgboost::DMatrix | Internal data structured used by XGBoost during training
C xgboost::common::RowSetCollection::Elem | Data structure to store an instance set, a subset of rows (instances) associated with a particular node in a decision tree
C xgboost::EllpackPage | A page stored in ELLPACK format
C xgboost::Entry | Element from a sparse vector
C xgboost::common::WQSummary< DType, RType >::Entry | Entry in the sketch summary
C xgboost::common::ExtremeDistribution |
►C false_type |
►C xgboost::common::detail::IsSpanOracle< std::remove_cv< T >::type > |
C xgboost::common::detail::IsSpan< T > |
C xgboost::common::detail::IsSpanOracle< T > |
C xgboost::FeatureMap | Feature map data structure to help text model dump. TODO(tqchen) consider make it even more lightweight
C xgboost::from_chars_result |
►C FunctionRegEntryBase |
C xgboost::GradientBoosterReg | Registry entry for tree updater
C xgboost::LinearUpdaterReg | Registry entry for linear updater
C xgboost::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"
C xgboost::ObjFunctionReg | Registry entry for objective factory functions
C xgboost::PredictorReg | Registry entry for predictor
C xgboost::TreeUpdaterReg | Registry entry for tree updater
C xgboost::RegTree::FVec | Dense feature vector that can be taken by RegTree and can be construct from sparse feature vector
C xgboost::common::GHistBuilder< GradientSumT > | Builder for histograms of gradient statistics
C xgboost::common::GHistIndexBlock |
C xgboost::common::GHistIndexBlockMatrix |
C xgboost::common::GHistIndexMatrix | Preprocessed global index matrix, in CSR format
C xgboost::detail::GradientPairInternal< T > | Implementation of gradient statistics pair. Template specialisation may be used to overload different gradients types e.g. low precision, high precision, integer, floating point
C xgboost::common::detail::Greater< T > |
C dmlc::serializer::Handler< xgboost::Entry > |
►C xgboost::IntrusivePtr< T >::Hash |
C std::hash< xgboost::IntrusivePtr< T > > |
C xgboost::common::HistCollection< GradientSumT > | Histogram of gradient statistics for multiple nodes
C xgboost::common::HistogramCuts |
C xgboost::HostDeviceVector< T > |
C xgboost::HostDeviceVector< bst_float > |
C xgboost::HostDeviceVector< bst_row_t > |
C xgboost::HostDeviceVector< FeatureType > |
C xgboost::HostDeviceVector< float > |
C xgboost::HostDeviceVector< uint32_t > |
C xgboost::HostDeviceVector< xgboost::Entry > |
C xgboost::HostDeviceVectorImpl< T > |
C xgboost::HostDeviceVectorImpl< bst_float > |
C xgboost::HostDeviceVectorImpl< bst_row_t > |
C xgboost::HostDeviceVectorImpl< FeatureType > |
C xgboost::HostDeviceVectorImpl< float > |
C xgboost::HostDeviceVectorImpl< uint32_t > |
C xgboost::HostDeviceVectorImpl< xgboost::Entry > |
C xgboost::common::HostSketchContainer |
C xgboost::HostSparsePageView |
C xgboost::common::Index |
►C integral_constant |
C xgboost::common::detail::ExtentAsBytesValue< T, Extent > |
C xgboost::common::detail::ExtentValue< Extent, Offset, Count > |
C xgboost::common::detail::IsAllowedElementTypeConversion< From, To > |
C xgboost::common::detail::IsAllowedExtentConversion< From, To > |
C xgboost::IntrusivePtr< T > | 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
C xgboost::IntrusivePtr< xgboost::Value > |
C xgboost::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
C xgboost::common::Range::Iterator |
C xgboost::Json | Data structure representing JSON format
C xgboost::JsonReader |
C xgboost::JsonWriter |
C xgboost::LearnerModelParam |
C xgboost::common::detail::Less< T > |
C xgboost::common::LogisticDistribution |
C xgboost::MetaInfo | Meta information about dataset, always sit in memory
►C xgboost::Model |
C xgboost::GradientBooster | Interface of gradient boosting model
C xgboost::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
C xgboost::RegTree | Define regression tree to be the most common tree model. This is the data structure used in xgboost's major tree models
C xgboost::common::Monitor | Timing utility used to measure total method execution time over the lifetime of the containing object
C xgboost::RegTree::Node | Tree node
C xgboost::common::NormalDistribution |
C xgboost::NumericLimits< T > |
C xgboost::NumericLimits< float > |
C xgboost::NumericLimits< int64_t > |
C xgboost::common::ParallelGHistBuilder< GradientSumT > | 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
C xgboost::common::ParallelGroupBuilder< ValueType, SizeType > | Multi-thread version of group builder
►C Parameter |
C xgboost::TreeParam | Meta parameters of the tree
C xgboost::XGBoostParameter< Type > |
►C xgboost::XGBoostParameter< AFTParam > |
C xgboost::common::AFTParam | Parameter structure for AFT loss and metric
►C xgboost::XGBoostParameter< GenericParameter > |
C xgboost::GenericParameter |
C xgboost::common::PartitionBuilder< BlockSize > |
C xgboost::BitFieldContainer< VT, Direction, IsConst >::Pos |
C xgboost::PredictionCacheEntry | Contains pointer to input matrix and associated cached predictions
C xgboost::PredictionContainer |
C xgboost::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
C xgboost::common::WQSummary< DType, RType >::Queue::QEntry |
C xgboost::common::QuantileSketchTemplate< DType, RType, TSummary > | Template for all quantile sketch algorithm that uses merge/prune scheme
►C xgboost::common::QuantileSketchTemplate< DType, unsigned, WQSummary< DType, unsigned > > |
C xgboost::common::WQuantileSketch< DType, RType > | Quantile sketch use WQSummary
►C xgboost::common::QuantileSketchTemplate< DType, unsigned, WXQSummary< DType, unsigned > > |
C xgboost::common::WXQuantileSketch< DType, RType > | Quantile sketch use WXQSummary
C xgboost::common::WQSummary< DType, RType >::Queue | Input data queue before entering the summary
C xgboost::common::Range |
C xgboost::common::Range1d |
C xgboost::common::RowSetCollection | Collection of rowset
C xgboost::RTreeNodeStat | Node statistics used in regression tree
C xgboost::RegTree::Segment |
►C Serializable |
C xgboost::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
C xgboost::JsonReader::SourceLocation |
C xgboost::common::Span< T, Extent > | Span class implementation, based on ISO++20 span<T>. The interface should be the same
C xgboost::common::Span< bst_row_t const > |
C xgboost::common::Span< const BinIdxType > |
C xgboost::common::Span< const size_t > |
C xgboost::common::Span< value_type > |
C xgboost::common::Span< xgboost::Entry const > |
C xgboost::common::detail::SpanIterator< SpanType, IsConst > |
►C xgboost::SparsePage | In-memory storage unit of sparse batch, stored in CSR format
C xgboost::CSCPage |
C xgboost::SortedCSCPage |
C xgboost::common::RowSetCollection::Split |
►C Stream |
C xgboost::common::Base64InStream | Stream that reads from base64, note we take from file pointers
C xgboost::common::Base64OutStream | Stream that write to base64, note we take from file pointers
►C xgboost::common::PeekableInStream | Input stream that support additional PeekRead operation, besides read
C xgboost::common::FixedSizeStream | A simple class used to consume ‘dmlc::Stream’ all at once
C xgboost::common::StreamBufferReader | Buffer reader of the stream that allows you to get
C xgboost::StringView |
►C Summary |
C xgboost::common::QuantileSketchTemplate< DType, RType, TSummary >::SummaryContainer | Same as summary, but use STL to backup the space
C xgboost::common::Timer |
C xgboost::to_chars_result |
C xgboost::TrainingObserver |
C xgboost::common::Transform< CompiledWithCuda > | Do Transformation on HostDeviceVectors
►C true_type |
C xgboost::common::detail::IsSpanOracle< Span< T, Extent > > |
►C xgboost::Value |
C xgboost::JsonArray |
C xgboost::JsonBoolean | Describes both true and false
C xgboost::JsonInteger |
C xgboost::JsonNull |
C xgboost::JsonNumber |
C xgboost::JsonObject |
C xgboost::JsonString |
C xgboost::Version |
►C xgboost::common::WQSummary< DType, RType > | Experimental wsummary
C xgboost::common::WXQSummary< DType, RType > | Try to do efficient pruning
C xgboost::XGBAPIThreadLocalEntry | Entry to to easily hold returning information
C XGBoostBatchCSR | Mini batch used in XGBoost Data Iteration