@Override
public Map<FieldName, ?> evaluate(ModelEvaluationContext context) {
SupportVectorMachineModel supportVectorMachineModel = getModel();
if (!supportVectorMachineModel.isScorable()) {
throw new InvalidResultException(supportVectorMachineModel);
}
SvmRepresentationType svmRepresentation = supportVectorMachineModel.getSvmRepresentation();
switch (svmRepresentation) {
case SUPPORT_VECTORS:
break;
default:
throw new UnsupportedFeatureException(supportVectorMachineModel, svmRepresentation);
}
Map<FieldName, ?> predictions;
MiningFunctionType miningFunction = supportVectorMachineModel.getFunctionName();
switch (miningFunction) {
case REGRESSION:
predictions = evaluateRegression(context);
break;
case CLASSIFICATION:
predictions = evaluateClassification(context);
break;
default:
throw new UnsupportedFeatureException(supportVectorMachineModel, miningFunction);
}
return OutputUtil.evaluate(predictions, context);
}
@Override
public Map<FieldName, ?> evaluate(ModelEvaluationContext context) {
TreeModel treeModel = getModel();
if (!treeModel.isScorable()) {
throw new InvalidResultException(treeModel);
}
Map<FieldName, ?> predictions;
MiningFunction miningFunction = treeModel.getMiningFunction();
switch (miningFunction) {
case REGRESSION:
predictions = evaluateRegression(context);
break;
case CLASSIFICATION:
predictions = evaluateClassification(context);
break;
default:
throw new UnsupportedFeatureException(treeModel, miningFunction);
}
return OutputUtil.evaluate(predictions, context);
}
@Override
public Map<FieldName, ?> evaluate(Map<FieldName, ?> arguments) {
RuleSetModel ruleSetModel = getModel();
if (!ruleSetModel.isScorable()) {
throw new InvalidResultException(ruleSetModel);
}
Map<FieldName, ?> predictions;
ModelManagerEvaluationContext context = new ModelManagerEvaluationContext(this);
context.pushFrame(arguments);
MiningFunctionType miningFunction = ruleSetModel.getFunctionName();
switch (miningFunction) {
case CLASSIFICATION:
predictions = evaluateRuleSet(context);
break;
default:
throw new UnsupportedFeatureException(ruleSetModel, miningFunction);
}
return OutputUtil.evaluate(predictions, context);
}