private void TrainAndEvaluateClassifier(Instances data, Instances testData, double splitStoppingConfidence, bool useGainRatio)
{
// learn the tree
ID3Learner learner = new ID3Learner(splitStoppingConfidence, true, useGainRatio);
Node decisionTree = learner.Learn(data);
// output the tree
File.WriteAllText(
string.Format("{0}_DTID3_{1}_{2}.txt", Path.GetFileNameWithoutExtension(this.trainingDataFilePath), useGainRatio, splitStoppingConfidence.ToString("0.0000")),
decisionTree.ToString());
// evaluate the classifier
DTClassifier classifier = new DTClassifier(decisionTree);
AccuracyEvaluator evaluator = new AccuracyEvaluator(classifier);
double accuracy = evaluator.Evaluate(testData);
this.reportData.Add(
string.Format("{0}\t\t\t{1}\t\t{2}{3}", splitStoppingConfidence.ToString("0.0000"), useGainRatio, accuracy.ToString("0.0000"), System.Console.Out.NewLine));
}
/// <summary>
/// Initializes a new instance of the AccuracyEvaluator class.
/// </summary>
/// <param name="classifier">classifier to evaluate</param>
public AccuracyEvaluator(DTClassifier classifier)
{
this.classifier = classifier;
}
