Firstly, I'd just like to say thank you to Jeff Heaton and everyone involved with Encog, excellent work guys. I've been playing with it for a few weeks now, both the workbench and the java version. I am quite new to Neural Networks, but I am learning fast and enjoying all the videos and materials.
Ok, now the questions:
1. In the java sunspot examples, the data is normalized to a high of 0.9 and a low of 0.1. Why is this? Seems to me that it should be between 0 and 1, or between -1 and 1.
2. In the PredictSunspotSVM.java example, if I understand the code correctly, there is only one training iteration, yet this example seems to be the most accurate of the three PredictSunspot examples. What is going on here?
3. In the PredictSunspotElman.java example, in the console after running, I see that a Predict value is printed for each line of both the Train and Evalu sections. Why does it predict while still training? Or am I completely off course in my thinking about this?
I'll stop there for now, but I do have many more questions.