xgboost
Class List
Here are the classes, structs, unions and interfaces with brief descriptions:
[detail level 12345]
 Ndmlc
 Nserializer
 NxgboostNamespace of xgboost
 Ncommon
 Ndetail
 CBatchIterator
 CBatchIteratorImpl
 CBatchParamParameters for constructing batches
 CBatchSet
 CBitFieldContainerA non-owning type with auxiliary methods defined for manipulating bits
 CConfigurable
 CCSCPage
 CDataSourceThis 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
 CDMatrixInternal data structured used by XGBoost during training. There are two ways to create a customized DMatrix that reads in user defined-format
 CEllpackPageA page stored in ELLPACK format
 CEntryElement from a sparse vector
 CFeatureMapFeature map data structure to help text model dump. TODO(tqchen) consider make it even more lightweight
 CFixedPrecisionStreamContainer
 CGenericParameter
 CGradientBoosterInterface of gradient boosting model
 CGradientBoosterRegRegistry entry for tree updater
 CHostDeviceVector
 CHostDeviceVectorImpl
 CJsonData structure representing JSON format
 CJsonArray
 CJsonBooleanDescribes both true and false
 CJsonInteger
 CJsonNull
 CJsonNumber
 CJsonObject
 CJsonReader
 CJsonString
 CJsonWriter
 CLBitsPolicy
 CLearnerLearner 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
 CLinearUpdaterInterface of linear updater
 CLinearUpdaterRegRegistry entry for linear updater
 CMetaInfoMeta information about dataset, always sit in memory
 CMetricInterface of evaluation metric used to evaluate model performance. This has nothing to do with training, but merely act as evaluation purpose
 CMetricRegRegistry 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
 CObjFunctionInterface of objective function
 CObjFunctionRegRegistry entry for objective factory functions
 CPredictionCacheEntryContains pointer to input matrix and associated cached predictions
 CPredictionContainer
 CPredictorPerforms 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
 CPredictorRegRegistry entry for predictor
 CRBitsPolicy
 CRegTreeDefine regression tree to be the most common tree model. This is the data structure used in xgboost's major tree models
 CRTreeNodeStatNode statistics used in regression tree
 CSortedCSCPage
 CSparsePageIn-memory storage unit of sparse batch, stored in CSR format
 CStringView
 CTrainingObserver
 CTreeParamMeta parameters of the tree
 CTreeUpdaterInterface of tree update module, that performs update of a tree
 CTreeUpdaterRegRegistry entry for tree updater
 CValue
 CVersion
 CXGBAPIThreadLocalEntryEntry to to easily hold returning information
 CXGBoostParameter
 CXGBoostBatchCSRMini batch used in XGBoost Data Iteration