xgboost

Class List
Here are the classes, structs, unions and interfaces with brief descriptions:
[detail level 1 2 3 4 5]

▼N dmlc |
►N serializer |
C Handler< xgboost::Entry > |
▼N std |
C hash< xgboost::IntrusivePtr< T > > |
▼N xgboost | Namespace of xgboost
►N common |
►N detail |
C ExtentAsBytesValue |
C ExtentValue |
C Greater |
C IsAllowedElementTypeConversion |
C IsAllowedExtentConversion |
C IsSpan |
C IsSpanOracle |
C IsSpanOracle< Span< T, Extent > > |
C Less |
C SpanIterator |
C AFTLoss | The AFT loss function
C AFTParam | Parameter structure for AFT loss and metric
C Base64InStream | Stream that reads from base64, note we take from file pointers
C Base64OutStream | Stream that write to base64, note we take from file pointers
C BlockedSpace2d |
C Column | 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 ColumnMatrix | Collection of columns, with support for construction from GHistIndexMatrix
C 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 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 CompressedIterator | Read symbols from a bit compressed memory buffer. Usable on device and host
C ConfigParser | Implementation of config reader
C DenseColumn |
C ExtremeDistribution |
C FixedSizeStream | A simple class used to consume ‘dmlc::Stream’ all at once
C GHistBuilder | Builder for histograms of gradient statistics
C HistCollection | Histogram of gradient statistics for multiple nodes
C HistogramCuts |
C HostSketchContainer |
C Index | Optionally compressed gradient index. The compression works only with dense data
C IndexTransformIter | Transform iterator that takes an index and calls transform operator
C IsCatOp |
C LogisticDistribution |
C MemStackAllocator | A C-style array with in-stack allocation. As long as the array is smaller than MaxStackSize, it will be allocated inside the stack. Otherwise, it will be heap-allocated
C Monitor | Timing utility used to measure total method execution time over the lifetime of the containing object
C NormalDistribution |
C OptionalWeights |
C ParallelGHistBuilder | 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 ParallelGroupBuilder | Multi-thread version of group builder
►C PartitionBuilder |
C BlockInfo |
C PeekableInStream | Input stream that support additional PeekRead operation, besides read
►C QuantileSketchTemplate | Template for all quantile sketch algorithm that uses merge/prune scheme
C SummaryContainer | Same as summary, but use STL to backup the space
►C Range |
C Iterator |
C Range1d |
►C RowSetCollection | Collection of rowset
C Elem | Data structure to store an instance set, a subset of rows (instances) associated with a particular node in a decision tree
C Split |
C Sched |
C SketchContainerImpl |
C SortedQuantile | Quantile structure accepts sorted data, extracted from histmaker
C SortedSketchContainer |
C Span | Span class implementation, based on ISO++20 span<T>. The interface should be the same
C SparseColumn |
C StreamBufferReader | Buffer reader of the stream that allows you to get
C Timer |
C Transform | Do Transformation on HostDeviceVectors
►C WQSummary | Experimental wsummary
C Entry | Entry in the sketch summary
►C Queue | Input data queue before entering the summary
C QEntry |
C WQuantileSketch | Quantile sketch use WQSummary
C WXQSummary | Try to do efficient pruning
C WXQuantileSketch | Quantile sketch use WXQSummary
►N detail |
C GradientPairInternal | Implementation of gradient statistics pair. Template specialisation may be used to overload different gradients types e.g. low precision, high precision, integer, floating point
►N linalg |
►N detail |
C AllTag |
C ArrayInterfaceHandler |
C IntTag |
C RangeTag |
C Tensor | 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
C TensorView | A tensor view with static type and dimension. It implements indexing and slicing
C BatchIterator |
C BatchIteratorImpl |
C BatchParam | Parameters for constructing batches
C BatchSet |
►C BitFieldContainer | A non-owning type with auxiliary methods defined for manipulating bits
C Pos |
C Configurable |
C CSCPage |
C DMatrix | Internal data structured used by XGBoost during training
C EllpackPage | A page stored in ELLPACK format
C Entry | Element from a sparse vector
C FeatureMap | Feature map data structure to help text model dump. TODO(tqchen) consider make it even more lightweight
C from_chars_result |
C GenericParameter |
C GlobalConfiguration |
C GradientBooster | Interface of gradient boosting model
C GradientBoosterReg | Registry entry for tree updater
C HostDeviceVector |
C HostDeviceVectorImpl |
C HostSparsePageView |
►C IntrusivePtr | 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 Hash |
C 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 Json | Data structure representing JSON format
C JsonArray |
C JsonBoolean | Describes both true and false
C JsonInteger |
C JsonNull |
C JsonNumber |
C JsonObject |
►C JsonReader |
C SourceLocation |
C JsonString |
C JsonTypedArray | Typed array for Universal Binary JSON
C JsonWriter |
C LBitsPolicy |
C 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 LearnerModelParam |
C LinearUpdater | Interface of linear updater
C LinearUpdaterReg | Registry entry for linear updater
C MetaInfo | Meta information about dataset, always sit in memory
C Metric | Interface of evaluation metric used to evaluate model performance. This has nothing to do with training, but merely act as evaluation purpose
C 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 Model |
C NumericLimits |
C NumericLimits< float > |
C NumericLimits< int64_t > |
C ObjFunction | Interface of objective function
C ObjFunctionReg | Registry entry for objective factory functions
C ObjInfo | 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
C PesudoHuberParam |
C PredictionCacheEntry | Contains pointer to input matrix and associated cached predictions
C PredictionContainer |
C 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 PredictorReg | Registry entry for predictor
C RBitsPolicy |
►C RegTree | Define regression tree to be the most common tree model. This is the data structure used in xgboost's major tree models
C CategoricalSplitMatrix |
C FVec | Dense feature vector that can be taken by RegTree and can be construct from sparse feature vector
C Node | Tree node
C Segment |
C RTreeNodeStat | Node statistics used in regression tree
C SortedCSCPage |
C SparsePage | In-memory storage unit of sparse batch, stored in CSR format
C StringView |
C to_chars_result |
C TrainingObserver |
C TreeParam | Meta parameters of the tree
C TreeUpdater | Interface of tree update module, that performs update of a tree
C TreeUpdaterReg | Registry entry for tree updater
C UBJReader | Reader for UBJSON https://ubjson.org/
C UBJWriter | Writer for UBJSON https://ubjson.org/
C Value |
C Version |
C XGBAPIThreadLocalEntry | Entry to to easily hold returning information
C XGBoostParameter |
C XGBoostBatchCSR | Mini batch used in XGBoost Data Iteration