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Hi, I think they should use the binary label since I found that the number of testing data stated by their paper is 13129. This is exactly the sum of data with age <=29 and >40
I asked the authors about this and they replied that they use 12 nodes for age classification with intervals from https://arxiv.org/abs/1809.02169. Unfortunately, I wasn't able to replicate the numbers with that setting though. Even the baseline numbers were off, so I asked for hyperparameters/other settings, but haven't heard back since then.
Also, treating this as binary classification problem would lose the distinction between age classification vs gender classification, so I think # of classes has to be different than 2.
How many output units do you use for age classification? Is each age a separate class? Or is it a binary problem 0-29 vs 40+?
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