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LimitedConsequence t1_j1d91l2 wrote

My first thought is to predict the 50 numbers simultaneously, and to apply softmax to the output (enforcing summing to 1), then scaling that so it sums to your desired number for each group.

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blablanonymous t1_j1dp14o wrote

If you just want to normalize everything why creating a custom activation function that just does that?

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LimitedConsequence t1_j1ep2ui wrote

I'm not sure I understand what you mean?

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blablanonymous t1_j1f4wy6 wrote

You’re suggesting Softmax then normalize to whatever is required. Softmax takes the exponential of the value then performs the normalization. You might not want that exponential. You can create a layer that does the normality through a custom activation function you use in the last layer

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LimitedConsequence t1_j1fdayy wrote

Yes I was implicitly talking about the final activation function. With regards to softmax, he said in another comment "I have a quantity of 100 units that need to be allocated across 50 days.", so I took that to imply the outputs should be positive (hence the exponential is reasonable).

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