Why in model.evaluate() from Keras the loss is used to calculate accuracy?

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Why in model.evaluate() from Keras the loss is used to calculate accuracy?



It may be a stupid question but:



I noticed that the choice of the loss function modifies the accuracy obtained during evaluation.



I thought that the loss was used only during training and of course from it depends the goodness of the model in making prediction but not the accuracy i.e amount of right predictions over the total number of samples.









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