Whats the output for Keras categorical_accuracy metrics?

Question

I cant find proper description of metrics outputs.

For example if I use

model.compile(loss='categorical_crossentropy', optimizer='adam', metrics=['accuracy'])

then I get loss and accuracy tr_loss, tr_acc = model.train_on_batch(X, Y)

if I compile with metrics=['categorical_accuracy'] then I get 2 numbers as well,

but what are they ?

EDIT: I did this: print(model.metrics_names) and got: ['loss', 'categorical_accuracy']

Possible duplicate of [What values are returned from model.evaluate() in Keras?](https://stackoverflow.com/questions/51299836/what-values-are-returned-from-model-evaluate-in-keras) — today, May 19 '19 at 14:47

Dr. Snoopy · Accepted Answer · 2019-05-19T14:59:11.870

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The accuracy metric is actually a placeholder and keras chooses the appropriate accuracy metric for you, between binary_accuracy if you use binary_crossentropy loss, and categorical_accuracy if you use categorical_crossentropy loss.

So in this specific case, both metrics (accuracy and categorical_accuracy) are literally the same, and model.evaluate return loss and accuracy.

edited May 19 '19 at 14:59

answered May 19 '19 at 14:54

Dr. Snoopy

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binary and category aren't the same at all. I have 8 categories and binary is only for 2. – Boppity Bop May 19 '19 at 14:58

Eric Yu · Answer 2 · 2019-05-20T05:28:53.077

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Could you please post the two numbers you mentioned? I guess they are loss (categorical_crossentropy in your case) and metrics you added. (accuracy or categorical_accuracy as configured in your case).

edited May 20 '19 at 05:28

answered May 19 '19 at 14:24

Eric Yu

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Whats the output for Keras categorical_accuracy metrics?

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