internal void CommitValues(FeatureBasedDCM model) { model.TrainingPointSpacing = TrainingPointSpacing; model.FeatureDistanceThreshold = FeatureDistanceThreshold; model.NegativePointStandoff = NegativePointStandoff; model.Classifier = Classifier; model.Features = Features; }
public new static IEnumerable <Feature> GetAvailableFeatures(Area area) { foreach (Feature f in FeatureBasedDCM.GetAvailableFeatures(area)) { yield return(f); } foreach (TimeSliceFeature f in Enum.GetValues(typeof(TimeSliceFeature))) { yield return(new Feature(typeof(TimeSliceFeature), f, null, null, f.ToString(), null)); } IFeatureExtractor externalFeatureExtractor = InitializeExternalFeatureExtractor(typeof(TimeSliceDCM)); if (externalFeatureExtractor != null) { foreach (Feature f in externalFeatureExtractor.GetAvailableFeatures(area)) { yield return(f); } } }
private void ok_Click(object sender, EventArgs e) { string errors = discreteChoiceModelOptions.ValidateInput() + featureBasedDcmOptions.ValidateInput(); if (errors != "") { MessageBox.Show(errors); return; } _resultingModel = featureBasedDcmOptions.FeatureBasedDCM; if (_resultingModel == null) { _resultingModel = new FeatureBasedDCM(); } discreteChoiceModelOptions.CommitValues(_resultingModel); featureBasedDcmOptions.CommitValues(_resultingModel); DialogResult = System.Windows.Forms.DialogResult.OK; Close(); }
public void Populate(FeatureBasedDCM m) { Items.Clear(); if (m != null) { Items.Add(m.Classifier); SetSelected(Items.IndexOf(m.Classifier), true); } foreach (Classifier available in Classifier.Available) { if (Items.Cast <Classifier>().Count(present => present.GetType().Equals(available.GetType())) == 0) { Items.Add(available); } } if (SelectedItem == null && Items.Count > 0) { SelectedIndex = 0; } }
public RandomForest(bool runFeatureSelection, FeatureBasedDCM model, int numTrees) : base(runFeatureSelection, model) { _numTrees = numTrees; }
public LibLinear(bool runFeatureSelection, FeatureBasedDCM model, PositiveClassWeighting positiveClassWeighting) : base(runFeatureSelection, model) { _positiveClassWeighting = positiveClassWeighting; }
public SvmRank(bool runFeatureSelection, FeatureBasedDCM model, float c) : base(runFeatureSelection, model) { _c = c; }
public FeatureBasedDcmForm(FeatureBasedDCM current) : this() { discreteChoiceModelOptions.DiscreteChoiceModel = featureBasedDcmOptions.FeatureBasedDCM = current; }
public FeatureBasedDcmForm() { InitializeComponent(); discreteChoiceModelOptions.trainingAreas.SelectedValueChanged += (o, e) => { featureBasedDcmOptions.TrainingArea = discreteChoiceModelOptions.TrainingArea; }; featureBasedDcmOptions.GetFeatures = new Func <Area, List <Feature> >(a => FeatureBasedDCM.GetAvailableFeatures(a).ToList()); discreteChoiceModelOptions.RefreshAreas(); }
public AdaBoost(bool runFeatureSelection, FeatureBasedDCM model, int iterations) : base(runFeatureSelection, model) { _iterations = iterations; }
protected Classifier(bool runFeatureSelection, FeatureBasedDCM model) { _model = model; _runFeatureSelection = runFeatureSelection; _numFeaturesInEachVector = -1; }