# Why don't we use trigonometric functions for the output neurons?

Why don't we use a trigonometric function, such as $$\tan(x)$$, where $$x$$ is an element of the interval $$[0,pi/2)$$, instead of the sigmoid function for the output neurons (in the case of classification)?

• Are you only interested in classification or also regression?
– nbro
Jun 23 '20 at 11:03
• In classification. I'm curious as to why we fit the data using a sigmoid function.
– AC18
Jun 23 '20 at 11:04

Trigonometric functions are periodic. In general, we may not want to convert a non-periodic function to a periodic one. To be more concrete, let's suppose we use the sine function as the activation function of the output neurons of a neural network. Assuming only one input, if the input to any of those output neurons is $$360k$$, for any integer $$k$$, the result will always be $$0$$, but that may not be desirable.