Hi KillerKhan,
For deep learning I've been more looking into libraries that use the GPU such as
http://gpumlib.sourceforge.net. You could use a Python script (a 'python predictor') to interface between DeepThought and those Java libraries.
I may look at GP sometime but from what I've read, for trading systems where the patterns are weak and buried in noise, GP has a tendency to overfit and doesn't perform well on out of sample data. I'll need to do some more research on this and see if anyone has solved the problem of how to control for overfitting.
Yes, this should be able to be done by changing the config for the bar series from
Code:
<bar-series>
<identifier>EURUSDh4</identifier>
<bar-series-type>const-time</bar-series-type>
<source type="bar-series">EURUSDm1</source>
<history-source-type>bar-series</history-source-type>
<price-to-pip-multiplier>10000.0</price-to-pip-multiplier>
<average-spread>0.0</average-spread>
<bar-duration-minutes>240</bar-duration-minutes>
<delay-minutes-offset>0</delay-minutes-offset>
</bar-series>
to
Code:
<bar-series>
<identifier>EURUSDh4</identifier>
<bar-series-type>const-time</bar-series-type>
<source type="bar-series">EURUSDm1</source>
<history-source-type>bar-series</history-source-type>
<price-to-pip-multiplier>10000.0</price-to-pip-multiplier>
<average-spread>0.0</average-spread>
[B]<bar-duration-minutes ga-subst="duration">240</bar-duration-minutes>[/B]
<delay-minutes-offset>0</delay-minutes-offset>
</bar-series>
and adding the following to the genetic algo section:
Code:
<genetic-algo>
...
<parameter id="duration" type="integer" low="10" high="360" step="10" />
...
</genetic-algo>
which will include durations of candles from 10 minutes to 6 hours in 10 minute increments.
If you want to limit the timeframes, use a categorical:
Code:
<parameter id="duration" type="categorical" values="20,45,60,90,120,180,240,360" />
Cheers
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