A classification model achieves 98% accuracy on the training set but only 62% accuracy on the validation set. What problem does this indicate and what is the most appropriate remedy?

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B. Overfitting; add regularization or reduce model complexity. A large gap between high training accuracy and low validation accuracy is the hallmark of overfitting — the model memorizes training data and fails to generalize. Regularization, dropout, early stopping, or reducing model complexity are standard remedies.

A classification model achieves 98% accuracy on the training set but only 62% accuracy on the validation set. What problem does this indicate and what is the most appropriate remedy?

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