As an example, If I had inputs of data that are then analyzed by Rapidminer I would take the analysis of that and need to input it into a Ninja strategy based on that analysis. What is the conduit between Ninja and Rapidminer? How does the information transfer?
Signed, Clueless in Programming/Scripting
Last edited by sam028; June 4th, 2010 at 03:20 AM.
This post has been selected as an answer to the original posters question
I dabbled with this for a while and used a lot of different data mining softwares as well as some homegrown versions. What you're going to need to do for this is to use the .dll files that are included with RapidMiner or whatever you do end up using. From there you will need to reference the saved model/network that you have trained.
It's probably best to use Visual Studio for this so that you can see what the .dll file references and how to access it. After you can access your network though, you should be fine. It's just a matter of taking the indicators and other inputs you trained it to use and plugging them in.
The best suites I used and the ones I had the most luck implementing in NinjaTrader were:
with AForge being an order of magnitude faster than Encog, although Encog is more fully-featured. At least in Java, I don't know if the C# library has caught up yet. Implementation between the two was almost exactly the same. If you need more guidance than that, I probably have some legacy code lying around for how to hook up to each one, but it'll take some searching.
Finally, I did notice you said "data mining" and a word of advice; I went through the same thing and what you should really be looking into is "time-series analysis", which is a whole different kind of analysis. Instead of looking at Neural Nets, Perceptrons, and Feedforward Backpropagation this or that, you should be looking at ANOVA and MANOVA(spelling?). However, if you do use Encog, I believe the have the Boltzmann machine is now a part of the library and I remember really wanting to look into that after looking at a few talks on the subject. I think there is a lot of promise there.
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