title: Disable Keras batch normalization/standardization
body: <p>I am using a simple Keras model for series prediction.</p>
  
  <p>I am feeding it input normalized across the entire series.</p>
  
  <p>The model prediction accuracy seems to be correct during training. However, when I plot the outputs of the <code>model.predict()</code> function, I can see that the outputs have been somehow scaled. It seems to be some kind of normalization/standardization type of scaling.</p>
  
  <p>Changing the batch size on training affects the result. I tried setting the batch size to the size of the input set, so that the training with the entire series is done in a single batch, which improves the result, but it is still scaled.</p>
  
  <p>My assumption is this has something to do with either normalization per input batch or output normalization. I do not have any <code>BatchNormalization</code> layers in my model.</p>
  
  <p>Is there a way to disable the default normalization/standardization of input/output in Keras (and does this default behavior exist)?</p>
  
  <p>I am using Keras 2 with Tensorflow backend and Tensorflow 1.1.</p>