pythonparametersjupyterxgboostml

None default values in XGBoost regressor model

I am encountering a problem regarding XGBoost regressor. It produces NONE' default values as shown in figure below. What could be the reason behind for getting 'NONE' default values for XSGBoost regressor Model.

enter image description here

How to sort out this problem. Moreover, I want to know on what basis we can apply parametrization to reduce the problem of overfitting. Thank you very much for any response.

Solution

  • As per the xgboost documentation (xgboost docs). Apart from the parameters such as "objective" by default points to square error, "enable_categorical" points to False, and "missing points" to nan. Apart from these parameters all others are optional which is None by default. So, you are getting none.

    You can print the entire parameters, using the below code to check it out. In your given model object-based display it is word wrapped to fit the display and line limits.

    # Get the default parameters
default_params = model.get_params()

# Print the default parameters
for param, value in default_params.items():
    print(f"{param}: {value}")