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I've used Classify[...] for a two class image classification problem which has yielded pretty good results. I let Mathematica select an algorithm for me and it picked a GBT model, everything looked good and the algorithm performed well.

I put the whole thing away for a while, but now it's come time to publish and although it's a small part of the study I feel I should know what loss function Mathematica chose for the model. I figured this would be easily accessible but I can't seem to find a citation or mention of this anywhere. I'm fairly certain it must use cross entropy, but "fairly certain" obviously isn't going to get past a reviewer.

If anyone has any idea, or knows how to get this information out of the model after training, I'd be very grateful if you could share your insights.

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  • $\begingroup$ Try evaluating List @@ classifier to see the information stored inside. That should reveal some information about the loss function as well. I'm going to go out on a limb and guess that it's mean crossentropy for a classification task. $\endgroup$ Commented May 17, 2021 at 21:11
  • $\begingroup$ This worked perfectly, and your guess was on the money. Thanks very much! If you want to post this as an answer I'll accept it. $\endgroup$ Commented May 18, 2021 at 13:11

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Try evaluating List @@ classifier to see the information stored inside. That should reveal some information about the loss function as well. I'm going to go out on a limb and guess that it's mean cross-entropy for a classification task.

Improve this answer
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