AWS Certified AI Practitioner AIF-C01 Practice Question
A team trains a text classification model that achieves 98 % accuracy on the training data but only 60 % on a held-out validation set. Which statement best describes the model's bias-variance condition?
The model has high variance, indicating overfitting to the training data.
The accuracy gap is due only to random noise; bias and variance are unaffected.
The model has high bias, indicating underfitting on both training and validation data.
The model demonstrates an optimal bias-variance tradeoff.
The large gap between training and validation accuracy means the model memorizes patterns specific to the training data and fails to generalize. This is characteristic of high variance, also called overfitting. High bias would show low accuracy on both datasets, an optimal tradeoff would have similar scores, and random noise alone cannot explain a consistent 38-percentage-point difference.
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AWS Certified AI Practitioner AIF-C01
Guidelines for Responsible AI
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