# What are the best activation functions for Binary text classification in neural networks?

I know that there are many activation functions like Relu, sigmoid, tanh ..etc, I just want to know the best one for my case - Binary text classification.

I have heard that Relu is best for Binary classification (not sure if im correct)

I have used keras to train a model, which is 2 layer , Dense 512, dropout 0.3, activation = "Relu" for these layers,

But the predictions are not upto the mark.

I have also changed the Dense units to 1024, keeping others same, but still I got bad predictions. (Validation accuracy 50%)

So, can i use other activations, or change my model layers (add few more layers) ??

What can be the best option ?

I guess you use a sequential, dense model architecture? Try to add more hidden layers. Don‘t add too much capacity for a start. You could try something like 256, 8, 8, 1 with relu.