So I kept running into this: GridSearchCV picks the model with the best validation score… but that model is often overfitting (train super high, test a bit inflated).
I wrote a tiny selector that balances:
how good the test score is how close train and test are (gap)
Basically, it tries to pick the “stable” model, not just the flashy one.
Code + demo here 👉heilswastik/FitSearchCV
submitted by /u/AdhesivenessOk3187 to r/learnmachinelearning
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