public static void TestTraining(this IClassifier c)
{
if (c.IsTrained)
{
throw new Exception("Already trained");
}
// IsTrained test
var examples = GetExamples();
var test = examples.SubView(0, (.1 * examples.Count).Rounded());
var train = examples.SubView(test.Count, examples.Count - test.Count);
c.Train(train);
if (!c.IsTrained)
{
throw new Exception("Classifier is trained");
}
// accuracy test
double minAccuracy = 0.6;
if (c.AccuracyOn(train) < minAccuracy && !(c.GetType() == typeof(DecisionStump) && c.AccuracyOn(train) > 0.5))
{
throw new Exception("Training accuracy < " + minAccuracy);
}
if (c.AccuracyOn(test) < minAccuracy && c.GetType() != typeof(DecisionStump))
{
throw new Exception("Test accuray < " + minAccuracy);
}
}
/// <summary>
/// Computes the classifier's error in predicting the set of examples
/// </summary>
public static double ErrorOn(this IClassifier classifier, IEnumerable <Example> labeledExamples)
{
return(1.0 - classifier.AccuracyOn(labeledExamples));
}