/*! * Copyright 2019 XGBoost contributors * * \file c-api-demo.c * \brief A simple example of using xgboost C API. */ #include #include #include #define safe_xgboost(call) { \ int err = (call); \ if (err != 0) { \ fprintf(stderr, "%s:%d: error in %s: %s\n", __FILE__, __LINE__, #call, XGBGetLastError()); \ exit(1); \ } \ } int main(int argc, char** argv) { int silent = 0; int use_gpu = 0; // set to 1 to use the GPU for training // load the data DMatrixHandle dtrain, dtest; safe_xgboost(XGDMatrixCreateFromFile("../data/agaricus.txt.train", silent, &dtrain)); safe_xgboost(XGDMatrixCreateFromFile("../data/agaricus.txt.test", silent, &dtest)); // create the booster BoosterHandle booster; DMatrixHandle eval_dmats[2] = {dtrain, dtest}; safe_xgboost(XGBoosterCreate(eval_dmats, 2, &booster)); // configure the training // available parameters are described here: // https://xgboost.readthedocs.io/en/latest/parameter.html safe_xgboost(XGBoosterSetParam(booster, "tree_method", use_gpu ? "gpu_hist" : "hist")); if (use_gpu) { // set the GPU to use; // this is not necessary, but provided here as an illustration safe_xgboost(XGBoosterSetParam(booster, "gpu_id", "0")); } else { // avoid evaluating objective and metric on a GPU safe_xgboost(XGBoosterSetParam(booster, "gpu_id", "-1")); } safe_xgboost(XGBoosterSetParam(booster, "objective", "binary:logistic")); safe_xgboost(XGBoosterSetParam(booster, "min_child_weight", "1")); safe_xgboost(XGBoosterSetParam(booster, "gamma", "0.1")); safe_xgboost(XGBoosterSetParam(booster, "max_depth", "3")); safe_xgboost(XGBoosterSetParam(booster, "verbosity", silent ? "0" : "1")); // train and evaluate for 10 iterations int n_trees = 10; const char* eval_names[2] = {"train", "test"}; const char* eval_result = NULL; for (int i = 0; i < n_trees; ++i) { safe_xgboost(XGBoosterUpdateOneIter(booster, i, dtrain)); safe_xgboost(XGBoosterEvalOneIter(booster, i, eval_dmats, eval_names, 2, &eval_result)); printf("%s\n", eval_result); } bst_ulong num_feature = 0; safe_xgboost(XGBoosterGetNumFeature(booster, &num_feature)); printf("num_feature: %llu\n", num_feature); // predict bst_ulong out_len = 0; const float* out_result = NULL; int n_print = 10; safe_xgboost(XGBoosterPredict(booster, dtest, 0, 0, 0, &out_len, &out_result)); printf("y_pred: "); for (int i = 0; i < n_print; ++i) { printf("%1.4f ", out_result[i]); } printf("\n"); // print true labels safe_xgboost(XGDMatrixGetFloatInfo(dtest, "label", &out_len, &out_result)); printf("y_test: "); for (int i = 0; i < n_print; ++i) { printf("%1.4f ", out_result[i]); } printf("\n"); // free everything safe_xgboost(XGBoosterFree(booster)); safe_xgboost(XGDMatrixFree(dtrain)); safe_xgboost(XGDMatrixFree(dtest)); return 0; }