I'm surprised you didn't post your question on the "Financial Neural
Networks" section of the forum but on the "Using encog in Java" instead!
You did see it right?
Just trying to help here... :-) . I'm genuinely interested in your
problem and I'd love to see the solution unfold! In fact if you get it
going I'd love to add it in the clojure-encog examples...
Jim
On 05/08/12 20:40, Timothy Washington wrote:
Hey Jim,
Yes, it absolutely crossed my mind to post this on the encog-java
forum. So I did just that (see here
<http://www.heatonresearch.com/node/2716>). Thanks very much for your
quick responses so far.
Tim Washington
Interruptsoftware.ca <http://Interruptsoftware.ca>
416.843.9060
On Sun, Aug 5, 2012 at 3:04 PM, Jim - FooBar(); <jimpil1...@gmail.com
<mailto:jimpil1...@gmail.com>> wrote:
Hi Tim,
first of all thanks for opening a new thread for this...
2 things :
The 1st paragraph is really a perfect question for the encog-java
forum...I'm not sure anyone here can help with this (not even me -
financial prediction with temporal data is one of those encog
corners I've not had the chance to look at or experiment yet)...I
do believe however that posting such a well phrased and genuinely
good question will attract attention, perhaps from Jeff Heaton
himself who you can think of as 'reliable'...just don't expect
things to go as quickly as they are going here on the clojure ml...
Now, on the 2nd part of your question which is actually about
clojure-encog...
Back over the clojure-encog, the thing that normalizes input
data, the make-data
<https://github.com/jimpil/clojure-encog/blob/master/src/clojure_encog/training.clj#L41>
function only deals with doubles (not a list of tick data entries).
the temporalDataset and foldedDataset (perhaps others too) have
not been wrapped yet...Patches are welcome if you get it going
finally... :). The most common ones (array-1d or array-2d) are
there though.
The make-trainer and train
<https://github.com/jimpil/clojure-encog/blob/master/src/clojure_encog/training.clj#L137>
functions seem to iterate for the number of strategies that
you've specified.
interrupting iterations can be done via a couple of
ways...generally, either you've got an iteration limit or some
error-tolerance that you aim for. strategies are completely
optional and have nothing to do with signalling end of
iterations...in fact, the XOR example works better without any
strategies whatsoever!
But I can't see in BackPropogation
<https://github.com/encog/encog-java-core/blob/master/src/main/java/org/encog/neural/networks/training/propagation/back/Backpropagation.java>
or it's superclass
<https://github.com/encog/encog-java-core/blob/master/src/main/java/org/encog/neural/networks/training/propagation/Propagation.java>,
where that tick data is actually processed (init and iteration
methods seem to just setup a background process). So I'm left
wondering how I can give the core encog neural-net a list of tick
data that has a second or sub-second granularity?
I think you're looking at the wrong place...the BackPropagation
class simply defines the algorithm - I don't think you will find
anything related with tick-data there...my bet would be the
temporalDataset class which is actually quite massive and scary!
again though, this is a perfectly valid question for the official
encog forum...You can expect Jeff or Seemagh to respond within the
week. I do remember some other guy very much interested in
financial predictions but he was doing everything in C#...
Hope that helps,
Jim
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