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Hello Barnix,
I have been working on PNN, found some implementations of it from fxreal.ru, have modified something, it works fine however, have to optimize sigma. I have been thinking if rbf-dda has been implemented, as far as understand it will find optimal sigma on its own during training process.
Here are the results of ea that works on pnn and trades on day close.
Symbol GBPUSDm (Great Britain Pound vs US Dollar)
Period Daily (D1) 2008.03.16 00:00 - 2008.05.15 00:00 (2008.03.16 - 2008.05.16)
Model Every tick (the most precise method based on all available least timeframes)
Parameters Lots=0.2; pBalanceTraded=1; adjustLotsOk=true; tradeAtDayClose=true; sl=140; tp=10; rp=0.7; pnn="----------pnn parameters----------"; sigma=0.1; fcastbars=2; Patterns=30; Inputs=6;
Bars in test 1053 Ticks modelled 505698 Modelling quality 90.00%
Mismatched charts errors 66
Initial deposit 1000.00
Total net profit 292.34 Gross profit 328.60 Gross loss -36.26
Profit factor 9.06 Expected payoff 18.27
Absolute drawdown 8.60 Maximal drawdown 68.01 (6.05%) Relative drawdown 6.05% (68.01)
Total trades 16 Short positions (won %) 11 (90.91%) Long positions (won %) 5 (80.00%)
Profit trades (% of total) 14 (87.50%) Loss trades (% of total) 2 (12.50%)
Largest profit trade 43.58 loss trade -31.58
Average profit trade 23.47 loss trade -18.13
Maximum consecutive wins (profit in money) 11 (217.01) consecutive losses (loss in money) 1 (-31.58)
Maximal consecutive profit (count of wins) 217.01 (11) consecutive loss (count of losses) -31.58 (1)
Average consecutive wins 7 consecutive losses 1
thanks Barnix for all of your ressources
i have joined other document, simple one to understand the theory,
sorry it's for French people, but it is comprehensible for others to undertand pnn algorithm (rbf, noyau)
i work a lot on these algorithm, and it's working very well. I work on M5 with 100000 examples, and 10 inputs (ema M5, ema H1, ema D1, sto)
i've got very good results in real, near Better one, i use PNN and not SVM machine, difficult to implement SVM algo
but i want to improve the ea,
i work now on optimization of sigma, wich is a very important parameter, i optimize it by a lot of simulation
now i want to use rbf-dda algorithm to optimize it, thanks a lot for the rbf-dda.mq4 file found here , i'm going to integrate it in my EA
i will give you my results soon
if someone have already works on rbf-dda, tell me, the more we are, the best we can do
Hello Barnix,
I have been working on PNN, found some implementations of it from fxreal.ru, have modified something, it works fine however, have to optimize sigma. I have been thinking if rbf-dda has been implemented, as far as understand it will find optimal sigma on its own during training process.
Here are the results of ea that works on pnn and trades on day close.
i work a lot on these algorithm, and it's working very well. I work on M5 with 100000 examples, and 10 inputs (ema M5, ema H1, ema D1, sto)
i've got very good results in real, near Better one, i use PNN and not SVM machine, difficult to implement SVM algo
Very interesting. I have been experimenting with NN and SVM. SVM performance is way less than NN but maybe I just have some problem in it. It seems that Barnix has made some progress with it but it is really hard to estimate results just from couple of screen shots. My SVM preforms really well on the training data but with test data it is just crap. NN is not too good either so I have not bothered to write EA yet.
Does your PNN perform best on M5 timeframe? Can you share any light on your outputs?