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suflaj t1_iyh2wil wrote

Well for softmax you need at least 2 neurons

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Santhosh999 OP t1_iykdg48 wrote

what about loss function I need to use?

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suflaj t1_iykea48 wrote

Doesn't matter. Softmax is just a multidimensional sigmoid. For binary classifications you can therefore use either 1 output and a sigmoid, or 2 outputs and a softmax. The only difference is that with a sigmoid you resolve the result as

is_fraud = result > 0.5

while with softmax you'd do

is_fraud = argmax(result) == 1
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Santhosh999 OP t1_iykgddd wrote

I am getting an error when tried with 2 neurons and softmax activation func with binary crossentropy loss.

ValueError: logits and labels must have the same shape ((None, 2) vs (None, 1))

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suflaj t1_iyktdbc wrote

Well, you have to change your labels from being 1 long to 2 long. If your labels are True or 1 and False or 0, you will need to change them to [0, 1] and [1, 0]

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Santhosh999 OP t1_iylsz52 wrote

Thanks for clearing my doubt. It is working now.

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