What function to use to transform real-vaued numbers to lables in classification task

[poster]

<p><a href="https://in.mathworks.com/help/deeplearning/gs/classify-patterns-with-a-neural-network.html" rel="nofollow noreferrer">https://in.mathworks.com/help/deeplearning/gs/classify-patterns-with-a-neural-network.html</a> explains how to apply multi layer perceptron for classification task. But it is unclear how to obtain the binary valued labels -- what function to use in the last layer. The model outputs real-valued numbers, so how to transform it to binary 0 and 1. In my dataset, the target is labelled either as 1 or 0 unlike the diagram given in the Matlab tutorial. So, my output layer contains 1 node. Once the model output is calculated, I can use a simple threshold function where all numbers greater than equal to 0.5 are labelled as 1 and the rest as zero. However, there must be some other functions or other thresholds as well. Can somebody please help in explaining how to obtain the labels? Thank you.</p>



More... (https://stackoverflow.com/questions/59014941/what-function-to-use-to-transform-real-vaued-numbers-to-lables-in-classification)