# Neural Network Multiple | Averging predictions

I am training multiple neural networks with various parameters. I am trying to average their predictions, but I am not really sure what that means, I am confused about what to average exactly. Here is what I mean: For a single observation in binary classification for example, the final node will give p a value between 0 and 1 (or -1 and 1 if you're using hyperbolic tangent Activation Function), then this p will be rounded to 1 or 0 if it's > 0.5, depending on your decision boundary.

Now, here is what I don't understand, should average p1, p2 and p3 produced by the models before rounding, or I should round the values to True/False responses and then compute the average? and how does that work exactly ?

• Can you specify the overview of the problem you are trying to solve... Ie. Binary classification, multi class classification, multi label classification Looks you are trying for Ensembling of various networks. – rajeshkumargp Oct 7 '19 at 17:52