private static string[] GetDetails(Classifier classifier, List <FeatureVector> vectors, TextIdMapper classToClassId, TextIdMapper featureToFeatureId)
{
TBLClassifier tblClassifier = (TBLClassifier)classifier;
var systemClasses = new int[vectors.Count];
var details = new string[vectors.Count];
for (int v_i = 0; v_i < vectors.Count; v_i++)
{
StringBuilder sb = new StringBuilder();
int currentClass = tblClassifier.DefaultClass;
foreach (TBLClassifier.Transformation t in tblClassifier.Transformations)
{
int newClass = tblClassifier.Transform(currentClass, t, vectors[v_i]);
if (newClass == currentClass)
{
continue;
}
string featName = featureToFeatureId[t.FeatureId];
string from_class = classToClassId[t.FromClass];
string to_class = classToClassId[t.ToClass];
sb.AppendFormat($" {featName} {from_class} {to_class}");
currentClass = newClass;
}
systemClasses[v_i] = currentClass;
details[v_i] = sb.ToString();
}
return(details);
}
// Methods
public override int ExecuteCommand()
{
FeatureVectorFile vectorFile = new FeatureVectorFile(path: vector_data, noOfHeaderColumns: 1, featureDelimiter: ':', isSortRequired: false);
int gold_i = 0;
TBLClassifier classifier = null;
Program.TrainModel(vectorFile, model_file, classifierFactory: (vectors, classToClassId, featureToFeatureId) =>
{
return(classifier = new TBLClassifier(vectors, classToClassId.Count, min_gain, gold_i));
}
);
return(classifier.Transformations.Count);
}
// Methods
public override double ExecuteCommand()
{
int gold_i = 0;
FeatureVectorFile vectorFile = new FeatureVectorFile(path: vector_file, noOfHeaderColumns: 1, featureDelimiter: ':', isSortRequired: false);
var accuracy = Program.ReportOnModel(vectorFile, sys_output
, classifierFactory: (classToClassId, featureToFeatureId) =>
{
return(TBLClassifier.LoadModel(model_file, classToClassId, featureToFeatureId, N, gold_i));
}
, getDetailsFunc: GetDetails
);
return(accuracy);
}
