public PerceptronCloud(double extraFactor = 2.0, PerceptronTrainingMode trainingMode = PerceptronTrainingMode.TRAIN_ALL_DATA, PerceptronClassificationMode classificationMode = PerceptronClassificationMode.NOFLAGS, double cloudSizeStDev = 0, bool normalizePerceptrons = true)
{
this.perceptronCountFactor = extraFactor;
this.trainingMode = trainingMode;
this.classificationMode = classificationMode;
this.cloudSizeStDev = cloudSizeStDev;
this.normalizePerceptrons = normalizePerceptrons;
}
public static IEnumerable <Tuple <string, IProbabalisticClassifier> > EnumeratePerceptrons(double oversamplingFactor)
{
foreach (PerceptronTrainingMode trainingMode in PerceptronTrainingMode.GetValues(typeof(PerceptronTrainingMode)))
{
foreach (PerceptronClassificationMode classificationMode in PerceptronClassificationMode.GetValues(typeof(PerceptronClassificationMode)))
{
foreach (bool normalize in new[] { false })
{
// foreach(bool normalize in new[]{true, false}){
foreach (double dist in new[] { 0, 1, 2 })
{
yield return(new Tuple <string, IProbabalisticClassifier>(
("Perceptron Cloud: t: " + trainingMode.ToString() + ", c: " + classificationMode.ToString() + ", " + "dist: " + dist + (normalize ? " (normalized out)" : "")).Replace("_", " "),
new PerceptronCloud(oversamplingFactor, trainingMode, classificationMode, dist, normalize)));
}
}
}
}
}
