public Prediction <LblT> Predict(string example)
{
Preconditions.CheckState(IsTrained);
example = FeatureProcessor.Run(example);
SparseVector <double> vector = BowSpace.ProcessDocument(example);
return(Model.Predict(vector));
}
public void Train(ILabeledExampleCollection <LblT, string> dataset)
{
Preconditions.CheckState(!IsTrained);
Preconditions.CheckNotNull(dataset);
Preconditions.CheckNotNull(BowSpace);
Preconditions.CheckNotNull(FeatureProcessor);
Preconditions.CheckNotNull(Model);
// preprocess the text
foreach (LabeledExample <LblT, string> le in dataset)
{
le.Example = FeatureProcessor.Run(le.Example);
}
// bow vectors
List <SparseVector <double> > bowData = BowSpace is DeltaBowSpace <LblT>
?(BowSpace as DeltaBowSpace <LblT>).Initialize(dataset as ILabeledDataset <LblT, string> ?? new LabeledDataset <LblT, string>(dataset))
: BowSpace.Initialize(dataset.Select(d => d.Example));
var bowDataset = new LabeledDataset <LblT, SparseVector <double> >();
for (int i = 0; i < bowData.Count; i++)
{
bowDataset.Add(dataset[i].Label, bowData[i]);
}
// train
if (OnTrainModel == null)
{
Model.Train(bowDataset);
}
else
{
OnTrainModel(this, bowDataset);
}
IsTrained = true;
}