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Comment commander un robot de trading dans MQL5 et MQL4
Voir un exemple de spécification des exigences pour commander un robot
Nouvelles commandes dans la catégorie:
5000+ USD
30+ USD
30 - 100 USD
35+ USD
100+ USD
Tâche terminée
Temps d'exécution 2 jours
Commentaires du client
It was a pleasure working with Mehmet. Nothing was too much trouble. Professional and punctual and understands the subject (Neural networks and backpropagation in my case) I would recommend him.
Spécifications
I need the backpropagation fixed in a Neural Network of an existing EA that will be used to take trades.
* Neural Network experience is essential *
* Do not apply if you do not understand Backpropagation, Calculus (the chain rule), (Stochastic) Gradient descent and error functions *
95% of the code described below already exists.
The input features already exist in the code.
Neural network structure:
One input layer
Three hidden layers
One Output layer (2 to 4 outputs depending on activation)
REQUIREMENTS:
Backpropagation using stochastic gradient descent
Loss/Error function
Update gradients
Update weights and biases in file
The network must learn
The weights and biases gradients must not explode or vanish
possible regularisation and normalization adjustments
The MQL4 code must compile with no errors and no warnings (property strict)
Clean existing code:
No libraries
No includes
No Errors
No Warnings
Clear well documented code
Variable names: use readable like trainingInputs[] rather than ti[] or x1[]
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The Existing code works like this:
Initialize:
Create random weights & biases in arrays
Write weights and biases to csv files
Train:
1) Load weights and biases from files into arrays (on each iteration)
2) Feed forward through NN (process input features)
3) Get a Buy or Sell signal (0 - 1) - EA takes a trade
4) Copy Feed Forward arrays to use at close of trade
(nothing happens until the trade closes)
5) When the trade closes, get the trade History Classify/Label the trade as buy/sell, profit/loss
6) Calculate error/cost function (using copied arrays)
7) Backpropagation (overwrite new adjusted weights and biases from updated arrays into files)
Repeat the process.
Trade:
Take trades using trained network
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Display on screen:
Trade quantity (considered as one labeled training example)
Last trade Ticket No.
Network output (predicted) eg. (0.2 | 0.8)
Actual (expected) output eg. ( 0 | 1)
Trade type: Buy/Sell/Hold
Trade result: M15 - GBPUSD | win/loss (1.2% SL and TP = 2.6 * SL) (12 pips SL and 32 pips TP)
% Error over the epoch - Loss/Trade quantity (I want to see if the network is learning)
Write to file:
Write the cost/iteration No. to file stats.csv (new line for each with epoch No.) so I can see or use the data to plot a graph in excel of the learn rate
I would like the code written in the same or similar style to mine.. (so I can understand the code and make any small changes in the future)
95% of the code already exists.
Timeframe: 2 days from start of job. Only take the job if and when you can start and complete in 2 days.
The budget is $150 - $200.
PAYMENT ON COMPLETION OF WORKING CODE ONLY.
Request the MQL4 file
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