private void AlgoritmAccurancy(weka.core.Instances insts, Classifier classifier, string algoritmName, bool?isNominal = null)
{
ClassifierManager manager = new ClassifierManager(insts);
manager.EliminateTargetAttribute();
if (isNominal == true)
{
manager.Discreatization(manager.Instance);
}
else if (isNominal == false)
{
manager.NominalToBinary(manager.Instance);
manager.Normalization(manager.Instance);
}
manager.Randomize(manager.Instance);
TrainModel model = manager.Train(manager.Instance, classifier);
SuccessfulAlgorithm.Add(new AlgorithmModel()
{
SuccessRatio = manager.FindAccurancy(),
AlgorithName = algoritmName,
TrainModel = model
});;
}
private void Btn_Click(object sender, EventArgs e)
{
bool isValid = true;
for (int j = 0; j < staticInsts.instance(0).numValues() - 1; j++)
{
if (!isValid)
{
break;
}
for (int i = 0; i < testValues.Count; i++)
{
if (testValues[i].GetType() == typeof(TextBox))
{
double res = 0;
if (!string.IsNullOrEmpty(((TextBox)testValues[i]).Text) &&
!double.TryParse(((TextBox)testValues[i]).Text, out res))
{
MessageBox.Show("Enter a valid value for " + labelNames[i]);
isValid = false;
break;
}
else if (string.IsNullOrEmpty(((TextBox)testValues[i]).Text))
{
MessageBox.Show("Enter a Value for " + labelNames[i]);
isValid = false;
break;
}
else
{
staticInsts.instance(0).setValue(i, Convert.ToDouble(((TextBox)testValues[i]).Text));
isValid = true;
}
}
else if (testValues[i].GetType() == typeof(ComboBox))
{
staticInsts.instance(0).setValue(i, ((ComboBox)testValues[i]).SelectedItem.ToString());
}
}
}
if (isValid)
{
ClassifierManager manager = new ClassifierManager(staticInsts);
if (algoritmName == "Naive Bayes")
{
manager.Discreatization(manager.Instance);
}
else if (algoritmName == "KNN with k = 3")
{
manager.NominalToBinary(manager.Instance);
manager.Normalization(manager.Instance);
}
double a = predictor.classifyInstance(manager.Instance.firstInstance());
string result = classes[(int)a];
MessageBox.Show("Result : " + result);
}
}
