#ifndef XGBOOST_WRAPPER_R_H_ #define XGBOOST_WRAPPER_R_H_ /*! * \file xgboost_wrapper_R.h * \author Tianqi Chen * \brief R wrapper of xgboost */ extern "C" { #include } extern "C" { /*! * \brief load a data matrix * \param fname name of the content * \param silent whether print messages * \return a loaded data matrix */ SEXP XGDMatrixCreateFromFile_R(SEXP fname, SEXP silent); /*! * \brief create matrix content from dense matrix * This assumes the matrix is stored in column major format * \param data R Matrix object * \param missing which value to represent missing value * \return created dmatrix */ SEXP XGDMatrixCreateFromMat_R(SEXP mat, SEXP missing); /*! * \brief create a matrix content from CSC format * \param indptr pointer to column headers * \param indices row indices * \param data content of the data * \return created dmatrix */ SEXP XGDMatrixCreateFromCSC_R(SEXP indptr, SEXP indices, SEXP data); /*! * \brief load a data matrix into binary file * \param handle a instance of data matrix * \param fname file name * \param silent print statistics when saving */ void XGDMatrixSaveBinary_R(SEXP handle, SEXP fname, SEXP silent); /*! * \brief set information to dmatrix * \param handle a instance of data matrix * \param field field name, can be label, weight * \param array pointer to float vector */ void XGDMatrixSetInfo_R(SEXP handle, SEXP field, SEXP array); /*! * \brief get info vector from matrix * \param handle a instance of data matrix * \param field field name * \return info vector */ SEXP XGDMatrixGetInfo_R(SEXP handle, SEXP field); /*! * \brief create xgboost learner * \param dmats a list of dmatrix handles that will be cached */ SEXP XGBoosterCreate_R(SEXP dmats); /*! * \brief set parameters * \param handle handle * \param name parameter name * \param val value of parameter */ void XGBoosterSetParam_R(SEXP handle, SEXP name, SEXP val); /*! * \brief update the model in one round using dtrain * \param handle handle * \param iter current iteration rounds * \param dtrain training data */ void XGBoosterUpdateOneIter_R(SEXP ext, SEXP iter, SEXP dtrain); /*! * \brief update the model, by directly specify gradient and second order gradient, * this can be used to replace UpdateOneIter, to support customized loss function * \param handle handle * \param dtrain training data * \param grad gradient statistics * \param hess second order gradient statistics */ void XGBoosterBoostOneIter_R(SEXP handle, SEXP dtrain, SEXP grad, SEXP hess); /*! * \brief get evaluation statistics for xgboost * \param handle handle * \param iter current iteration rounds * \param dmats list of handles to dmatrices * \param evname name of evaluation * \return the string containing evaluation stati */ SEXP XGBoosterEvalOneIter_R(SEXP handle, SEXP iter, SEXP dmats, SEXP evnames); /*! * \brief make prediction based on dmat * \param handle handle * \param dmat data matrix * \param output_margin whether only output raw margin value */ SEXP XGBoosterPredict_R(SEXP handle, SEXP dmat, SEXP output_margin); /*! * \brief load model from existing file * \param handle handle * \param fname file name */ void XGBoosterLoadModel_R(SEXP handle, SEXP fname); /*! * \brief save model into existing file * \param handle handle * \param fname file name */ void XGBoosterSaveModel_R(SEXP handle, SEXP fname); /*! * \brief dump model into text file * \param handle handle * \param fname file name of model that can be dumped into * \param fmap name to fmap can be empty string */ void XGBoosterDumpModel_R(SEXP handle, SEXP fname, SEXP fmap); }; #endif // XGBOOST_WRAPPER_R_H_