Within the bias-variance tradeoff, what characteristic fundamentally describes an overfit model?
Answer
High variance, making the model overly sensitive to the specific data points contained in the training set.
High variance means that if the model is trained again on a slightly different sample from the same distribution, the resulting parameters would differ significantly, showing sensitivity to sample-specific noise rather than stable underlying patterns.
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