[FEATURE] Run with given regressor instead of raising warning in ZeroInflatedRegressor

I am using the ZeroInflatedRegressor for the prediction of some materials’ prices. For some materials I am getting this error:

Traceback (most recent call last):
  File "/home/bugra/project-mats/mat_analyser.py", line 61, in apply_regression
    zir.fit(X_train, y_train)
  File "/home/bugra/project-mats/mats_folder/lib/python3.7/site-packages/sklego/meta/zero_inflated_regressor.py", line 107, in fit
    "The predicted training labels are all zero, making the regressor obsolete. Change the classifier or use a plain regressor instead.")
ValueError: The predicted training labels are all zero, making the regressor obsolete. Change the classifier or use a plain regressor instead.

Tbh. I didn’t understand much from the error. But, I guess using the regressor (in my case this is LinearRegression from sklearn) could give me some results. Why ZeroInflatedRegressor can’t use the regressor I defined for it but instead raising this error? I think there should be a flag (a parameter) in ZeroInflatedRegressor which would let it fit the regressor as suggested by the error message if the user wants. If not, it could still raise this error.

[MBrouns]

I’m thinking something along the lines of handle_unknown in sklearns OneHotEncoder

ZeroInflatedRegressor(handle_zero='error')
ZeroInflatedRegressor(handle_zero='ignore')

[DoDzilla-ai]

@koaning I wish I could, currently struggling with health issues 😦