How does Sigmoid activation work in multi-class classification problems
If your task is a kind of classification that the labels are mutually exclusive, each input just has one label, you have to use Softmax. If the inputs of your classification task have multiple labels for an input, your classes are not mutually exclusive and you can use Sigmoid for each output. For the former case, you should choose the output entry with the maximum value as the output. For the latter case, for each class, you have an activation value which belongs to the last sigmoid. If each activation is more than 0.5 you can say that entry exists in the input.