void fg_Values(double[] featureVectors)
{
int action = model.Classify(featureVectors);
foreach (var key in model.ActionList.Keys)
{
if (AsyncWorkerProcess != null && model.ActionList[key] == action)
{
AsyncWorkerProcess.ReportProgress(action, key);
}
}
}
/// <summary>
/// Calculates Mean Square Error based on supplied test data and previously calculated model
/// </summary>
/// <returns>returns Mean Square Error</returns>
public double Test()
{
double error = 0;
for (int i = 0; i < testDataInput.Length; i++)
{
int actualValue = _ml.Classify(testDataInput[i]);
double delta = testDataOutput[i][0] - actualValue;
error += delta * delta;
}
double mse = error / _er.FeatureVectorsOutputInput.Count;
this.Error = mse;
this.TimeElapsedSeconds = (DateTime.Now - startTime).TotalSeconds.ToString();//"{0:hh\\:mm\\:ss\\:fffffff}",
return(mse);
}
