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AWS Certified AI Practitioner · AWS
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Accuracy= Total predictions / Number of correct predictions If you see how many were correctly classified then it is Accuracy (binary & multiclass) If you see regression values then it is R² or RMSE (predicting continuous values) No metric called Learning rate Classification metrics These apply when theproblem is classification (e.g., predicting illness vs healthy, disease types, etc.): Accuracy , AUC, BalancedAccuracy ,F1 score ,F1macro ,Precision , PrecisionMacro ,Recall ,RecallMacro —,LogLoss — Regression metrics For regression tasks (predicting continuous values): MAE — mean absolute error , MSE — mean squared error. Other metrics InferenceLatency (useful for performance diagnostics).
B is correct.
Accuracy is a common metric for evaluating image classification , when the accuracy is high, it generally means the model is performing well by making a higher proportion of correct predictions.