public static ConfusionMatrix[] GetConfusionMatrixes(Model.Hierarchical.IHierarchicalClassifier classifier, List <Data.Dataset> testingSets)
{
DataMining.Model.Hierarchical.LocalClassifier localClassifier = classifier as DataMining.Model.Hierarchical.LocalClassifier;
ConfusionMatrix[] list = new ConfusionMatrix[testingSets[0].Metadata.Target.Values.Length];
for (int exmapleIndex = 0; exmapleIndex < testingSets[0].Size; exmapleIndex++)
{
List <Data.Example> examples = new List <Data.Example>();
foreach (Data.Dataset testset in testingSets)
{
examples.Add(testset[exmapleIndex]);
}
int[] predicted = localClassifier.Classify(examples);
int[] actual = testingSets[0][exmapleIndex].HierarchicalLabel;
for (int classIndex = 0; classIndex < list.Length; classIndex++)
{
if (predicted.Contains(classIndex))
{
if (actual.Contains(classIndex))
{
list[classIndex].TP++;
}
else
{
list[classIndex].FP++;
}
}
else
{
if (actual.Contains(classIndex))
{
list[classIndex].FN++;
}
else
{
list[classIndex].TN++;
}
}
}
}
return(list);
}
public static ConfusionMatrix[] GetConfusionMatrixes(Model.Hierarchical.IHierarchicalClassifier classifier, Data.Dataset testset)
{
ConfusionMatrix[] list = new ConfusionMatrix[testset.Metadata.Target.Values.Length];
foreach (Data.Example example in testset)
{
int[] predicted = classifier.Classify(example);
int[] actual = example.HierarchicalLabel;
for (int classIndex = 0; classIndex < list.Length; classIndex++)
{
if (predicted.Contains(classIndex))
{
if (actual.Contains(classIndex))
{
list[classIndex].TP++;
}
else
{
list[classIndex].FP++;
}
}
else
{
if (actual.Contains(classIndex))
{
list[classIndex].FN++;
}
else
{
list[classIndex].TN++;
}
}
}
}
return(list);
}
