linkedin / linkedin/photon-ml

The best model's RMSE score doesn't match ..

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Description

The best model's RMSE score doesn't match what's given by the validation data when scored by the best model.

I pass the following to the GameTrainingDriver:

...
--input-data-directories "glmm_in/train_data.avro" \
--validation-data-directories "glmm_in/test_data.avro" \
...

And, receive:

Best model has RMSE score of 10.212347636694373 and following config: ....

I'm assuming that the best model's RMSE score is computed on the validation data provided.
Yet, when I score the validation data using the best model and compute the RMSE score, the result is quite different from the best score announced.

Is the best score indeed based on the validation data?
Is a non-standard definition of RMSE being used here?
What could I be doing wrong? (Btw, the difference is significant enough to matter.)

Regards.

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Research direction

Start at the GameTrainingDriver invocation and trace how --input-data-directories and --validation-data-directories are used to calculate the reported best-model RMSE. Compare that calculation with scoring test_data.avro using the selected model, including the RMSE definition. Done means the discrepancy is explained and the expected scoring behavior is clear.

Written by the indexing model from the issue text.

Assessment

Tech stack
spark
Domain
machine-learning
Issue type
Bug
Difficulty
4/5
Estimated time
3-5 days
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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