//JAVA TO C# CONVERTER WARNING: Method 'throws' clauses are not available in .NET:
//ORIGINAL LINE: public boolean predict(org.maltparser.core.feature.FeatureVector featureVector, org.maltparser.parser.history.action.SingleDecision decision) throws org.maltparser.core.exception.MaltChainedException
public virtual bool predict(FeatureVector featureVector, SingleDecision decision)
{
AtomicModel model = getAtomicModel((SingleFeatureValue)featureVector.FeatureModel.DivideFeatureFunction.FeatureValue);
if (model == null)
{
if (Guide.Configuration.LoggerInfoEnabled)
{
Guide.Configuration.logInfoMessage("Could not predict the next parser decision because there is " + "no divide or master model that covers the divide value '" + ((SingleFeatureValue)featureVector.FeatureModel.DivideFeatureFunction.FeatureValue).IndexCode + "', as default" + " class code '1' is used. ");
}
decision.addDecision(1); // default prediction
return(true);
}
return(model.predict(getModelFeatureVector(model, featureVector), decision));
}
/// <summary>
/// Adds a candidate to the k-best list
/// </summary>
/// <param name="actionCode"> the integer representation of candidate action </param>
/// <exception cref="MaltChainedException"> </exception>
//JAVA TO C# CONVERTER WARNING: Method 'throws' clauses are not available in .NET:
//ORIGINAL LINE: public void add(int actionCode) throws org.maltparser.core.exception.MaltChainedException
public virtual void add(int actionCode)
{
if (k != -1 && addCandidateIndex >= k)
{
return;
}
if (addCandidateIndex >= kBestList.Count)
{
kBestList.Add(new Candidate());
}
kBestList[addCandidateIndex].ActionCode = actionCode;
if (addCandidateIndex == 0)
{
// if (decision instanceof SingleDecision) {
// ((SingleDecision)decision).addDecision(actionCode);
// }
decision.addDecision(actionCode);
topCandidateIndex++;
}
addCandidateIndex++;
}
//JAVA TO C# CONVERTER WARNING: Method 'throws' clauses are not available in .NET:
//ORIGINAL LINE: public boolean predict(org.maltparser.core.feature.FeatureModel featureModel, org.maltparser.parser.history.action.ComplexDecisionAction decision, boolean one_prediction) throws org.maltparser.core.exception.MaltChainedException
public bool predict(FeatureModel featureModel, ComplexDecisionAction decision, bool one_prediction)
{
if (decision.numberOfDecisions() > 2)
{
throw new MaltChainedException("Number of decisions is greater than two, which is unsupported in the light-weight parser (lw.parser)");
}
featureModel.update();
bool success = true;
for (int i = 0; i < decision.numberOfDecisions(); i++)
{
LWClassifier classifier = null;
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final org.maltparser.parser.history.action.SingleDecision singleDecision = decision.getSingleDecision(i);
SingleDecision singleDecision = decision.getSingleDecision(i);
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final StringBuilder classifierString = new StringBuilder();
StringBuilder classifierString = new StringBuilder();
//JAVA TO C# CONVERTER WARNING: The original Java variable was marked 'final':
//ORIGINAL LINE: final StringBuilder decisionModelString = new StringBuilder();
StringBuilder decisionModelString = new StringBuilder();
if (singleDecision.RelationToNextDecision == RelationToNextDecision.BRANCHED)
{
decisionModelString.Append("bdm");
}
else if (singleDecision.RelationToNextDecision == RelationToNextDecision.SEQUANTIAL)
{
decisionModelString.Append("sdm");
}
else
{
decisionModelString.Append("odm");
}
decisionModelString.Append(i);
string decisionSymbol = "";
if (i == 1 && singleDecision.RelationToNextDecision == RelationToNextDecision.BRANCHED)
{
decisionSymbol = singleDecision.DecisionSymbol;
decisionModelString.Append(decisionSymbol);
}
decisionModelString.Append('.');
FeatureVector featureVector = featureModel.getFeatureVector(decisionSymbol, singleDecision.TableContainer.TableContainerName);
if (featureModel.hasDivideFeatureFunction())
{
SingleFeatureValue featureValue = (SingleFeatureValue)featureModel.DivideFeatureFunction.FeatureValue;
classifierString.Append(decisionModelString);
classifierString.Append(string.Format("{0:D3}", featureValue.IndexCode));
classifierString.Append('.');
classifierString.Append(classifierName);
classifier = classifiers[classifierString.ToString()];
if (classifier != null)
{
FeatureVector dividefeatureVector = featureModel.getFeatureVector("/" + featureVector.SpecSubModel.SubModelName);
success = classifier.predict(dividefeatureVector, singleDecision, one_prediction) && success;
continue;
}
classifierString.Length = 0;
}
classifierString.Append(decisionModelString);
classifierString.Append(classifierName);
classifier = classifiers[classifierString.ToString()];
if (classifier != null)
{
success = classifier.predict(featureVector, singleDecision, one_prediction) && success;
}
else
{
singleDecision.addDecision(1);
}
if (!singleDecision.continueWithNextDecision())
{
break;
}
}
return(success);
}