A model can score exceptionally well in a notebook and still fail on genuinely new data. One common reason is data leakage: information that would not be available at prediction time has influenced training or evaluation.
A model can score exceptionally well in a notebook and still fail on genuinely new data. One common reason is data leakage: information that would not be available at prediction time has influenced training or evaluation.