Binary Step Activation Function
Binary Step is the simplest threshold-based activation function which works by either activating the node, i.e. passing on its output to the next layer in case the threshold value is surpassed, or doing nothing at all.
Mathematically, it can be defined as:
If the node input value is less than 0, it returns 0 as output. Else, it returns 1.
Usage and Limitations
As the name suggests, binary step can be used as an activation function in the output layer of a neural network for binary classification problems.
It is generally not suggested to use binary step in the hidden layer as it is a linear piecewise function unable to handle complex representations.
The following is an example of the activation function in Python:
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