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Hi
I got trained DRLearner model here:
dr_best = DRLearner(
model_propensity=propensity_best,
model_regression=outcome_best,
model_final=final_best,
categories='auto',
discrete_outcome=True,
random_state=1,
cv=1 )
dr_best.fit(Y=Y_full, T=T_fulli, X=X_full)I got 3 treatments and 1 control group.
After training I saved model with pickle.
At that point, everything is fine.
So whenever I try to load the model on differenet server I got this error:
NotFittedError: Estimator not fitted, call fit before exploiting the model.
After that I try to save models one by one (extracting sklearn wrapper and reach the models) but I couldnt get the same predictions (I use model.effect() in order to get scores).
I asked this situation to ChatGPT and I got this answer:
Because:
LightGBM booster C++ binary
Pickle doesn't guarantee binary compatibility
Therefore, this happens:
"The model was fitted, but it's not considered fitted here"
This is a transport problem, not a training problem.
I also checked the environment library versions of both server, everthing is same. So how can I solve this problem?
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