title: How is the hidden layer size determined for MLPRegressor in SciKitLearn?
body: <p>Lets say I'm creating a neural net using the following code:</p>
  
  <pre><code>from sklearn.neural_network import MLPRegressor
  
  model = MLPRegressor(
    hidden_layer_sizes=(100,),
    activation='identity'
  )
  model.fit(X_train, y_train)
  </code></pre>
  
  <p>For the <code>hidden_layer_sizes</code>, I simply set it to the default. However, I don't really understand how it works. What is the number of hidden layers in my definition? Is it 100?</p>