Hi, I am slightly confused and would like to know the difference between a softmax output and a multi label output given they would have same number of units depends on the number of labels you want to classify

Hi, @Nnaemeka_Nwankwo !

Multi-label output refers to a generalization of multiclass classification which involves predicting mutually non-exclusive class labels.

With softmax, when one logit (the unnormalized output of a model) is higher pushes the other logits to be smaller. Intuitively, it does the opposite of what you would want to achive in a multi-label problem, which is actually having several output logits high (meaning high probability)

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Thank you Alvaro, I now have better understanding since they are â€śmutually non-exclusiveâ€ť so each will have a high probability if itâ€™s true. Thanks.