Hello,
I have a question about handling test datasets in XGBoost. Here's my current approach:
- I'm using 10-fold cross-validation for model training and validation
- I keep a separate test dataset completely excluded during this training phase (hide and exclude in the table before launching the model)
- After training, I manually generate predictions on this test dataset (save predicted to table and I unhide the test data)
My issue is: By handling the test data separately, I'm missing out on the automatic performance metrics that XGBoost can calculate. Is there a way to:
- Keep the test data completely segregated during training (using hide and exclude)
- BUT still have XGBoost automatically calculate performance metrics on this test data after training is complete?
