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;
}
