PNN for metatrader using Parzen window classification version 2 with kernel smoothing of inputs

This is the PNN using Parzen window classification version 2 with kernel smoothing of inputs. You need to have the PFE indicator.

Here you will file the standard PNN called version 2. And the PNN with money management and kernel smoothing of inputs.

Nevertheless this is a beta version, because I am not sure that the integration of the kernel smoothing with the PNN code is correctly executed.

So this is what we have for now. Anyway the idea is interesting.

In the normal PNN Eric we have as input the difference between:


b[bar]= Close[bar]-Open[bar+AmoutOfForecastBars-1])

The idea was to replace this piece of code with something else and to see how it would affect the EA.

So I replaced this by the kernel smoothing of PFE.


b[bar] = kernel()

So this is the idea. However the number of bars of parameters is still an important parameter because it affects the initial period for training:


TrainingStartTime = Time[0] + Period()*60*AmoutOfForecastBars

Of course we can replace this piece of code by Numbars_for_Training as a parameter, but I chose not to touch this for the moment.


TrainingStartTime = Time[0] + Period()*Numbars_for_Training

Any wise look in the code would be welcome as there is not many native mql code for neural implementations.

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