/** * Create an instance of {@link Scorecard } * */ public Scorecard createScorecard() { return new Scorecard(); }
@Override public VisitorAction accept(Visitor visitor) { VisitorAction status = visitor.visit(this); if (status == VisitorAction.CONTINUE) { visitor.pushParent(this); if ((status == VisitorAction.CONTINUE)&&hasExtensions()) { status = PMMLObject.traverse(visitor, getExtensions()); } if (status == VisitorAction.CONTINUE) { status = PMMLObject.traverse(visitor, getMiningSchema(), getOutput(), getModelStats(), getModelExplanation(), getTargets(), getLocalTransformations(), getCharacteristics(), getModelVerification()); } visitor.popParent(); } if (status == VisitorAction.TERMINATE) { return VisitorAction.TERMINATE; } return VisitorAction.CONTINUE; }
Scorecard scorecard = getModel(); boolean useReasonCodes = scorecard.isUseReasonCodes(); Value<V> score = valueFactory.newValue(scorecard.getInitialScore()); Characteristics characteristics = scorecard.getCharacteristics(); for(Characteristic characteristic : characteristics){ Double baselineScore = null; baselineScore = characteristic.getBaselineScore(); if(baselineScore == null){ baselineScore = scorecard.getBaselineScore(); Scorecard.ReasonCodeAlgorithm reasonCodeAlgorithm = scorecard.getReasonCodeAlgorithm(); switch(reasonCodeAlgorithm){ case POINTS_ABOVE:
Scorecard scorecard = new Scorecard(MiningFunction.REGRESSION, ModelUtil.createMiningSchema(schema.getLabel()), characteristics) .setInitialScore(formatScore((basePoints.asScalar()).doubleValue() - Math.log((odds.asScalar()).doubleValue()) * factor - (intercept != null ? intercept * factor : 0))) .setUseReasonCodes(false);
public ScorecardEvaluator(PMML pmml, Scorecard scorecard){ super(pmml, scorecard); Characteristics characteristics = scorecard.getCharacteristics(); if(characteristics == null){ throw new MissingElementException(scorecard, PMMLElements.SCORECARD_CHARACTERISTICS); } // End if if(!characteristics.hasCharacteristics()){ throw new MissingElementException(characteristics, PMMLElements.CHARACTERISTICS_CHARACTERISTICS); } }
@Override public Scorecard addExtensions(org.dmg.pmml.Extension... extensions) { getExtensions().addAll(Arrays.asList(extensions)); return this; }
@Override public Scorecard addExtensions(org.dmg.pmml.Extension... extensions) { getExtensions().addAll(Arrays.asList(extensions)); return this; }
@Override public VisitorAction accept(Visitor visitor) { VisitorAction status = visitor.visit(this); if (status == VisitorAction.CONTINUE) { visitor.pushParent(this); if ((status == VisitorAction.CONTINUE)&&hasExtensions()) { status = PMMLObject.traverse(visitor, getExtensions()); } if (status == VisitorAction.CONTINUE) { status = PMMLObject.traverse(visitor, getMiningSchema(), getOutput(), getModelStats(), getModelExplanation(), getTargets(), getLocalTransformations(), getCharacteristics(), getModelVerification()); } visitor.popParent(); } if (status == VisitorAction.TERMINATE) { return VisitorAction.TERMINATE; } return VisitorAction.CONTINUE; }
/** * Create an instance of {@link Scorecard } * */ public Scorecard createScorecard() { return new Scorecard(); }
@Test public void inspectTypeAnnotations(){ PMML pmml = createPMML(); assertVersionRange(pmml, Version.PMML_3_0, Version.PMML_4_3); pmml.addModels(new AssociationModel(), //new ClusteringModel(), //new GeneralRegressionModel(), //new MiningModel(), new NaiveBayesModel(), new NeuralNetwork(), new RegressionModel(), new RuleSetModel(), new SequenceModel(), //new SupportVectorMachineModel(), new TextModel(), new TreeModel()); assertVersionRange(pmml, Version.PMML_3_0, Version.PMML_4_3); pmml.addModels(new TimeSeriesModel()); assertVersionRange(pmml, Version.PMML_4_0, Version.PMML_4_3); pmml.addModels(new BaselineModel(), new Scorecard(), new NearestNeighborModel()); assertVersionRange(pmml, Version.PMML_4_1, Version.PMML_4_3); pmml.addModels(new BayesianNetworkModel(), new GaussianProcessModel()); assertVersionRange(pmml, Version.PMML_4_3, Version.PMML_4_3); }