private Dictionary <int, double> CreateThresholds(UnivariateAlgorithmInput algorithmInput)
{
AlgorithmInputData data = algorithmInput.data;
thresholds = new Dictionary <int, double>();
for (int i = 0; i < data.input.Length; i++)
{
int classIndex = data.output[i];
if (GestureDataManager.GetClassName(classIndex) != "Nothing")
{
double distance = ComputeDistance(data.input[i], registers[classIndex]);
if (!thresholds.ContainsKey(classIndex))
{
thresholds[classIndex] = distance;
}
else
{
thresholds[classIndex] = Math.Max(thresholds[classIndex], distance);
}
}
}
List <int> keys = thresholds.Keys.ToList();
foreach (int key in keys)
{
thresholds[key] *= 2;
}
return(thresholds);
}
public override double ComputeError(AlgorithmInputData data)
{
Assert.IsTrue(data.input.Length == data.output.Length && data.input.Length > 0, "The length should be equal - input : " + data.input.Print() + " output : " + data.output.Print());
Assert.IsTrue(data.input[0].Length > 10, "The data is too short :" + data.input[0].Print());
double nbFalse = 0;
double nbTrue = 0;
for (int i = 0; i < data.input.Length; i++)
{
if (GestureDataManager.GetClassName(data.output[i]) != "Nothing")
{
List <string> errors;
if (!(Recognize(data.input[i], out errors).ContainsKey(data.output[i])))
{
nbFalse++;
}
else
{
nbTrue++;
}
}
}
double error = nbFalse / (nbFalse + nbTrue);
return(error);
}
public abstract double ComputeError(AlgorithmInputData input);
