public void DeltaRuleLearning_Test_iterations_1000_learningrate_02()
{
loadRealDataSample(); // System coefficients initialization.
var desc = loadMetaData(); // Description of the system.
LearningApi api = new LearningApi(desc);
//Real dataset must be defined as object type, because data can be numeric, binary and classification
api.UseActionModule <double[, ], double[, ]>((input, ctx) =>
{
return(loadRealDataSample()); // return actual System coefficients data
});
// run input = UseActionModule output
//run Delta Rule for 1000 iterations with learningRate=0.2
api.UseDeltaRuleLearning(0.2, 1000);
var result = api.Run() as double[];
Debug.WriteLine("************ Output Predictions***********");
for (int i = 0; i < result.Length; i++)
{
if (result[i] != 0)
{
Debug.WriteLine(result[i]);
}
}
using (var fs = File.OpenRead(@"H_Test.csv"))
using (var reader = new StreamReader(fs))
{
while (!reader.EndOfStream)
{
var line = reader.ReadLine();
var values = line.Split(',');
ti = new double[values.Length];
to = new double[values.Length];
for (int i = 0; i < values.Length; i++)
{
var val = values[i].Split(' ');
double.TryParse(val[0], out x);
double.TryParse(val[1], out y);
ti[i] = x;
to[i] = y;
}
}
}
for (int i = 0; i < to.Length; i++)
{
//Testing of Test data with Predicted System model
Assert.Equal(Math.Round(result[i], 4), Math.Round(to[i], 4));
}
}
