On the link of XGBoost guide:
After training, the model can be saved. bst.save_model(\'0001.model\') The model a
After training, the model can be saved.
bst.save_model(\'0001.model\')
The model a
An easy way of saving and loading a xgboost model is with joblib library.
import joblib #save model joblib.dump(xgb, filename) #load saved model xgb = joblib.load(filename)