/// <summary>
///
/// </summary>
/// <param name="inputVariable"></param>
/// <param name="inputVariableValue"></param>
/// <returns></returns>
public ClassCategory GetDecision(PatternClassificationInput inputVariable, int inputVariableValue)
{
// MatlabInterface.Execute request
MatlabInterface.Execute("inputClassifierDecision = " + ClassifierUniqueId + ".InputNodeClassifiers(" + inputVariable.ClassifierMatlabIndex + ").getDecision(" + inputVariableValue + ");");
// fetch value and return
var intResult = MatlabInterface.MatlabVariableToInteger("inputClassifierDecision", true);
var c = _classificationCategories[intResult - 1];
return(c);
}
/// <summary>
///
/// </summary>
/// <param name="inputVariable"></param>
/// <param name="inputVariableValue"></param>
/// <param name="c"></param>
/// <param name="plot"></param>
public void AssociateWithCategory(PatternClassificationInput inputVariable, int inputVariableValue,
ClassCategory c, bool plot)
{
// associate input value with cateogiry, for the specified variable
MatlabInterface.Execute(ClassifierUniqueId + " = " + ClassifierUniqueId + ".InputNodeClassifiers(" + inputVariable.ClassifierMatlabIndex + ").createAssociation(" + inputVariableValue + ", " + c.MatlabIndex + ");");
// plot
if (plot)
{
MatlabInterface.Execute(ClassifierUniqueId + " = " + ClassifierUniqueId + ".InputNodeClassifiers(" + inputVariable.ClassifierMatlabIndex + ").plotLikelihoods();");
}
}
/// <summary>
/// On user selecting/deselecting listviewitem in Input Nodes listview
/// </summary>
/// <param name="sender"></param>
/// <param name="e"></param>
private void listOfInputNodes_itemsSelectedOrDeselected(object sender, EventArgs e)
{
if (listInputNodes.SelectedItems.Count > 0)
{
_selectedInputNode = (PatternClassificationInput)listInputNodes.SelectedItems[0].Tag;
OnNewInputNodeSelected();
}
else
{
_selectedInputNode = null;
OnSelectedInputNodeCleared();
}
}
/// <summary>
///
/// </summary>
/// <param name="inputVariable"></param>
/// <param name="priorProbabilities"></param>
public void SetCategoryPriories(PatternClassificationInput inputVariable, double[] priorProbabilities)
{
var matlabArrayName = "newPrioriesForInputNo_" + inputVariable.ClassifierMatlabIndex;
MatlabInterface.ArrayToMatlabVector(priorProbabilities, matlabArrayName, true);
if (priorProbabilities.Length != _classificationCategories.Count)
{
throw new ApplicationException(
"Number of priories in array does not match number of classification categories!");
}
MatlabInterface.Execute(ClassifierUniqueId + " = " + ClassifierUniqueId + ".setCategoryPrioriesForInput(" + inputVariable.ClassifierMatlabIndex +
", " + matlabArrayName + ");");
// plot resultant priories of BC
MatlabInterface.Execute("plot(" + ClassifierUniqueId + ".InputNodeClassifiers(" + inputVariable.ClassifierMatlabIndex +
").priories);");
}
