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deep-learningpytorchloss

What is the multi-label binary classification?

Reading PyTorch docs BCEWithLogitsLoss:

where c is the class number (c > 1 for multi-label binary classification, c = 1 for single-label binary classification), nn is the number of the sample in the batch and p_cp c is the weight of the positive answer for the class cc .

What is the multi-label binary classification? Binary assume only two labels AFIK

Solution

  • Multi-label in terms of binary classification means that both the classes can be true class for a single example.

    For example, in case of dog-cat classifier, for an image containing both dog and cat, it'll predict both dog and cat.

    In the multi-label problem there is no constraint on how many of the classes the instance can be assigned to. Wiki