public static Edu.Stanford.Nlp.Classify.OneVsAllClassifier <L, F> Train <L, F>(IClassifierFactory <string, F, IClassifier <string, F> > classifierFactory, GeneralDataset <L, F> dataset, ICollection <L> trainLabels)
{
IIndex <L> labelIndex = dataset.LabelIndex();
IIndex <F> featureIndex = dataset.FeatureIndex();
IDictionary <L, IClassifier <string, F> > classifiers = Generics.NewHashMap();
foreach (L label in trainLabels)
{
int i = labelIndex.IndexOf(label);
logger.Info("Training " + label + " = " + i + ", posIndex = " + posIndex);
// Create training data for training this classifier
IDictionary <L, string> posLabelMap = new ArrayMap <L, string>();
posLabelMap[label] = PosLabel;
GeneralDataset <string, F> binaryDataset = dataset.MapDataset(dataset, binaryIndex, posLabelMap, NegLabel);
IClassifier <string, F> binaryClassifier = classifierFactory.TrainClassifier(binaryDataset);
classifiers[label] = binaryClassifier;
}
Edu.Stanford.Nlp.Classify.OneVsAllClassifier <L, F> classifier = new Edu.Stanford.Nlp.Classify.OneVsAllClassifier <L, F>(featureIndex, labelIndex, classifiers);
return(classifier);
}