I would like to build a simple neural network with ENCOG to perform classification. I found a example that shows XOR. There is a double array that contains inputs and another array that contains ideal outputs for the learning process. So the dataset looks like this:
/// Input f o r the XOR f unc t i on .
public static double [ ] [ ] XORInput = {
new[ ] { 0.0 , 0.0 },
new[ ] { 1.0 , 0.0 },
new[ ] { 0.0 , 1.0 },
new[ ] { 1.0 , 1.0}
} ;
/// I d e a l output f o r the XOR f unc t i on .
public static double [ ] [ ] XORIdeal = {
new[ ] { 0.0 } ,
new[ ] { 1.0 } ,
new[ ] { 1.0 } ,
new[ ] {0.0}
} ;
// create training data
IMLDataSet trainingSet = new BasicMLDataSet(XORInput, XORIdeal);
Then the network it self is created and here is the learning process initialized
// train the neural network
IMLTrain train = new ResilientPropagation(network, trainingSet);
Now I would like to know how can I load my own dataset from a txt files so I can use it instead of XORInput, XORIdeal.
I have tried:
string[] ins = File.ReadAllLines(path);
double [] inputs = new double[ins.Length]
for(int i=0; i<ins.Length; i++)
{
inputs[i] = Double.Parse(ins[i]);
}
EDIT: This is how my inputs looks like:
166 163 180 228
165 162 160 226
166 163 180 228
166 164 180 228
171 162 111 225
And OUT:
0 0 1
0 0 1
0 1 0
1 0 0
0 1 0
This is not working. I assume that its because I do not have every one element of txt files indexed. I am stucked here. Can anyone help please? Thank you.
OK, a quick snippet:
using System.Linq;
public static class Load {
public static double[][] FromFile(string path) {
var rows = new List<double[]>();
foreach (var line in File.ReadAllLines(path)) {
rows.Add(line.Split(new[]{' '}).Select(double.Parse).ToArray());
}
return rows.ToArray();
}
}
Call like XORInput = Load.FromFile("C:\\...");
Hopefully if you pick through that it should become clear.