本文介绍了在C ++中使用XGBOOST的处理方法,对大家解决问题具有一定的参考价值,需要的朋友们下面随着小编来一起学习吧!

问题描述

如何使用XGBOOST 库C ++?我已经建立了Python和Java API,但是找不到用于c ++的API

How can I use XGBOOST https://github.com/dmlc/xgboost/ library in c++? I have founded Python and Java API, but I can't found API for c++

推荐答案

我最终使用了C API,参见下面的示例:

I ended up using the C API, see below an example:

// create the train data
int cols=3,rows=5;
float train[rows][cols];
for (int i=0;i<rows;i++)
    for (int j=0;j<cols;j++)
        train[i][j] = (i+1) * (j+1);

float train_labels[rows];
for (int i=0;i<rows;i++)
    train_labels[i] = 1+i*i*i;


// convert to DMatrix
DMatrixHandle h_train[1];
XGDMatrixCreateFromMat((float *) train, rows, cols, -1, &h_train[0]);

// load the labels
XGDMatrixSetFloatInfo(h_train[0], "label", train_labels, rows);

// read back the labels, just a sanity check
bst_ulong bst_result;
const float *out_floats;
XGDMatrixGetFloatInfo(h_train[0], "label" , &bst_result, &out_floats);
for (unsigned int i=0;i<bst_result;i++)
    std::cout << "label[" << i << "]=" << out_floats[i] << std::endl;

// create the booster and load some parameters
BoosterHandle h_booster;
XGBoosterCreate(h_train, 1, &h_booster);
XGBoosterSetParam(h_booster, "booster", "gbtree");
XGBoosterSetParam(h_booster, "objective", "reg:linear");
XGBoosterSetParam(h_booster, "max_depth", "5");
XGBoosterSetParam(h_booster, "eta", "0.1");
XGBoosterSetParam(h_booster, "min_child_weight", "1");
XGBoosterSetParam(h_booster, "subsample", "0.5");
XGBoosterSetParam(h_booster, "colsample_bytree", "1");
XGBoosterSetParam(h_booster, "num_parallel_tree", "1");

// perform 200 learning iterations
for (int iter=0; iter<200; iter++)
    XGBoosterUpdateOneIter(h_booster, iter, h_train[0]);

// predict
const int sample_rows = 5;
float test[sample_rows][cols];
for (int i=0;i<sample_rows;i++)
    for (int j=0;j<cols;j++)
        test[i][j] = (i+1) * (j+1);
DMatrixHandle h_test;
XGDMatrixCreateFromMat((float *) test, sample_rows, cols, -1, &h_test);
bst_ulong out_len;
const float *f;
XGBoosterPredict(h_booster, h_test, 0,0,&out_len,&f);

for (unsigned int i=0;i<out_len;i++)
    std::cout << "prediction[" << i << "]=" << f[i] << std::endl;


// free xgboost internal structures
XGDMatrixFree(h_train[0]);
XGDMatrixFree(h_test);
XGBoosterFree(h_booster);

这篇关于在C ++中使用XGBOOST的文章就介绍到这了,希望我们推荐的答案对大家有所帮助,也希望大家多多支持!

10-21 06:46