NNBuilder

Building Neural Network Models Node by Node.

AdaScale: This NNBuilder version attempts adaptive scaling/preprocessing. Implementation in progress.

In a nutshell:

Before optimizing a new node the pseoudo-response gets preprocessed with a new scaler

Predictions are made recrusively by:

	add prediction from the most recent node
		apply most recent postprocessing
			add prediction from previous node
				apply previous postprocessing
					.....
						add prediction from 0th node
							apply 0th postprocessing 

Expected benefits:

	Each node can recreate limited behavior.
	While the original pre-processing puts the data in a form
	that simplifies this task, we have no guarantee that any of
	the pseudo-responses after the 1st node are still in this "easy to handle" form.
	To get around this problem, we adaptively scale/preprocess pseudo-response
	to simplify learning for each node.
	Also, by maintaining mean 0 and variance 1 gaussian with b=1 
	may learn more effectively than other nodes.
	But first this idea will be tested with sigmoidal nodes only.