Predict JRSX, using NS2 in XAUUSD 60 minutes data, 8549 rows:
1. Input: JRSX (t), JRSX (t+1),JRSX (t+2),JRSX (t+3),JRSX (t+4), JRSX(t+5)
afterward named them as variable I0 to I6
2. Output: JRSX(t-5) as variable O
Here is sample code defining input and output Neural network:
for( shift=i; shift>=1; shift--)
{
input[0] = iCustom(NULL,0, "aaJRSX", 0,14,0,0, shift);
input[1] = iCustom(NULL,0, "aaJRSX", 0,14,0,0, shift+1);
input[2] = iCustom(NULL,0, "aaJRSX", 0,14,0,0, shift+2);
input[3] = iCustom(NULL,0, "aaJRSX", 0,14,0,0, shift+3);
input[4] = iCustom(NULL,0, "aaJRSX", 0,14,0,0, shift+4);
input[5] = iCustom(NULL,0, "aaJRSX", 0,14,0,0, shift+5);
output[0]= iCustom(NULL,0, "aaJRSX", 0,14,0,0, shift-5);
}
3. Neural Network architecture in NS2: Back Propagation, Wards Net, 3 hidden slabs, 7 input neuron, 1 output neuron. Training criteria: rotation, turboprop, 80% data for training and 20% for testing.
See attached training data (in a zip), input-output and training result: I achieve only 0.6321 (less than 2 minutes optimization).