title: Set up different actiavtion functions for different layers using "neuralnet" package
body: <p>Ciao,
  I am working to neuralnet in R.
  I used to program this kind of stuff using Keras in python so I would expect to be able to set up different activation functions for different layers.</p>
  
  <p>Let me explain. Suppose I want to build a neural net with 2 hidden layers (say with 5 and 4 neurons) and an output between -1 and 1.</p>
  
  <p>I would like to set up <em>RELU</em> or <em>softplus</em> in the hidden layers and <em>tanh</em> in the output layer.</p>
  
  <p>The issue here is that <em>neuralnet</em> package lets me choose only one activation function via the argument <em>act.fun</em>:</p>
  
  <pre><code>&gt; nn &lt;- neuralnet(data = data, hidden = c(5, 4), act.fun =tanh)
  </code></pre>
  
  <p>I tried by setting the act.fun argument as <strong>c(softplus, softplus, tanh)</strong> but of course I get an error because the <em>neuralnet</em> function expects only one function for that argument.</p>
  
  <p>Do you know how I can set up the neuralnet in this way? On the internet I can only find very basic linear neural net built with this package. If it would be not possible this mean that this package is almost useless because it would be able to build only "linear models" (??!)</p>
  
  <p>Thanks a lot,
  ciao</p>