private Dictionary <GestureType, Result> DoExperimentOnDataset(Dictionary <GestureType, List <GestureSample> > RecognitionSamples,
string experimentName)
{
Dictionary <GestureType, Result> accuracy = new Dictionary <GestureType, Result>();
Console.WriteLine("*********************************************************************************");
Console.WriteLine("Running User Independent Experiment(" + ExperimentNo + ") On : " + experimentName);
//do classification on Samples
foreach (GestureType gType in Config.GesturesToUse)
{
List <GestureSample> samplesToRecognize = RecognitionSamples[gType];
accuracy.Add(gType, new Result());
accuracy[gType].Total = samplesToRecognize.Count;
foreach (GestureSample gSample in samplesToRecognize)
{
GestureType classification = Recognizer.Classify(gSample);
if (classification == gType)
{
accuracy[gType].Correct++;
}
}
Console.WriteLine("Accuracy[" + gType + "] : " + accuracy[gType].Correct + "/" + accuracy[gType].Total + " ~= " + accuracy[gType].Accuracy);
}
//report accuracy
float average = 0.0f;
float min = float.PositiveInfinity, max = float.NegativeInfinity;
foreach (GestureType gType in Config.GesturesToUse)
{
average += accuracy[gType].Accuracy;
if (accuracy[gType].Accuracy > max)
{
max = accuracy[gType].Accuracy;
}
if (accuracy[gType].Accuracy < min)
{
min = accuracy[gType].Accuracy;
}
}
Console.WriteLine(String.Format("accuracy: {0}, \t[Min: {1}, Max: {2}]", (average / (float)Config.GesturesToUse.Count), min, max));
Console.WriteLine("*********************************************************************************");
return(accuracy);
}
public static void TestLC()
{
//double[][] input = new double[][]
//{
// new double[]{0,0,0},
// new double[]{0,0,1},
// new double[]{0,1,0},
// new double[]{0,1,1},
// new double[]{1,0,0},
// new double[]{1,0,1},
// new double[]{1,1,0},
// new double[]{1,1,1}
//};
//bool[] result = new bool[]
//{
// false,
// false,
// false,
// false,
// false,
// false,
// false,
// true
//};
double[][] input = new double[][]
{
new double[] { 0, 0 },
new double[] { 0, 1 },
new double[] { 1, 0 },
new double[] { 1.1, 1.1 }
};
bool[] result = new bool[]
{
true,
false,
false,
true
};
LinearClassifier LC = new LinearClassifier(input, result);
while (true)
{
try
{
Console.WriteLine("Eingabe: ");
double[] loop = new double[2];
for (int i = 0; i < 2; ++i)
{
loop[i] = Convert.ToDouble(Console.ReadLine());
}
Console.WriteLine("Ergebniss: " + LC.Classify(loop).ToString());
}
catch
{
Console.WriteLine("Fehler bei der Eingabe");
}
}
}