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))); } } } } }