I have a vector of length $n \gt 4$ which has exactly 4 targets, so for example [0, 0, 0, 1, 0, 1, 0, 1, 1]. I would like to know how I can modify the softmax function for this case. Usually, it is normalized so that all probabilities sum to 1. In my case, all the probabilities will need to sum to 4 -- is there any way to do this?
Topic multi-output softmax multiclass-classification
Category Data Science
If I understand your question correctly, you are trying to find a function that "normalizes"/scales every vector to a vector with norm 4?
Usually, you could scale your vector with any feature-scaling method (see wikipedia for more details). After you have normalized this simply multiply it with 4 to rescale the normalized vectors.
I hope this is what you were looking for.
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