At the output layer of a binary classification problem, we could either use sigmoid
activation function with single output neuron or softmax function with two neurons, to
produce similar results.
For a classification application, that predicts whether a task is personal or official and
which also predicts whether it is high or low priority, we could use two output neuron
and apply sigmoid activation function on each output neuron.
For a classification application, that predicts whether Team A would win, lose or draw
the match, we could use three output neurons with softmax activation function applied
at the output layer.
Fig: 1