What condition defines the presence of overfitting in a machine learning model?
Answer
It performs brilliantly on training data but fails miserably on new, unseen examples.
Overfitting occurs when a model learns the training data too well, capturing not only the true patterns but also memorizing the random noise and idiosyncrasies specific to that set, leading to poor performance on external data.
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