@Override public String apply(Object object){ return ValueUtil.formatValue(object); } };
@Override public String apply(Integer integer){ return ValueUtil.formatValue(integer); } };
@Override public String apply(Object object){ String targetCategory = ValueUtil.formatValue(object); if(targetCategory == null || ("").equals(targetCategory)){ throw new IllegalArgumentException(targetCategory); } // End if if(!(targetCategory).equals(targetCategory.trim())){ throw new IllegalArgumentException(targetCategory); } return targetCategory; } };
@Override public void encode(Node node, LeafNode leafNode){ String score = ValueUtil.formatValue(leafNode.prediction()); node.setScore(score); } };
@Override public void decorate(DataField dataField, MiningField miningField){ super.decorate(dataField, miningField); if(invalidValueReplacement != null){ miningField.setInvalidValueReplacement(ValueUtil.formatValue(invalidValueReplacement)); } } }
@Override public VisitorAction visit(Node node){ Integer id = Integer.valueOf(node.getId()); Object value = values.get(id); if(value != null){ value = ScalarUtil.decode(value); addExtension((Node & HasExtensions)node, ValueUtil.formatValue(value)); } return super.visit(node); } };
@Override public VisitorAction visit(Value pmmlValue){ Object value = values.get(pmmlValue.getValue()); if(value != null){ value = ScalarUtil.decode(value); addExtension(pmmlValue, ValueUtil.formatValue(value)); } return super.visit(pmmlValue); } };
outputValues.add(ValueUtil.formatValue(coefficient)); .setDefaultValue(ValueUtil.formatValue(0d));
@Override public List<Feature> encodeFeatures(List<Feature> features, SkLearnEncoder encoder){ List<?> classes = getClasses(); ClassDictUtil.checkSize(1, features); Feature feature = features.get(0); List<String> inputCategories = new ArrayList<>(); List<String> outputCategories = new ArrayList<>(); for(int i = 0; i < classes.size(); i++){ inputCategories.add(ValueUtil.formatValue(classes.get(i))); outputCategories.add(ValueUtil.formatValue(i)); } Supplier<MapValues> mapValuesSupplier = () -> { encoder.toCategorical(feature.getName(), inputCategories); return PMMLUtil.createMapValues(feature.getName(), inputCategories, outputCategories); }; DerivedField derivedField = encoder.ensureDerivedField(FeatureUtil.createName("label_encoder", feature), OpType.CATEGORICAL, DataType.INTEGER, mapValuesSupplier); Feature encodedFeature = new CategoricalFeature(encoder, derivedField, outputCategories); Feature result = new CategoricalFeature(encoder, feature, inputCategories){ @Override public ContinuousFeature toContinuousFeature(){ return encodedFeature.toContinuousFeature(); } }; return Collections.singletonList(result); }
String category = ValueUtil.formatValue(entry.getKey()); String value = ValueUtil.formatValue(entry.getValue());
@Override public List<Feature> encodeFeatures(List<Feature> features, SkLearnEncoder encoder){ List<? extends Number> values = getValues(); ClassDictUtil.checkSize(1, features); Feature feature = features.get(0); List<Feature> result = new ArrayList<>(); if(feature instanceof CategoricalFeature){ CategoricalFeature categoricalFeature = (CategoricalFeature)feature; ClassDictUtil.checkSize(values, categoricalFeature.getValues()); for(int i = 0; i < values.size(); i++){ result.add(new BinaryFeature(encoder, categoricalFeature, categoricalFeature.getValue(i))); } } else if(feature instanceof WildcardFeature){ WildcardFeature wildcardFeature = (WildcardFeature)feature; List<String> categories = new ArrayList<>(); for(int i = 0; i < values.size(); i++){ int value = ValueUtil.asInt(values.get(i)); String category = ValueUtil.formatValue(value); categories.add(category); result.add(new BinaryFeature(encoder, wildcardFeature, category)); } wildcardFeature.toCategoricalFeature(categories); } else { throw new IllegalArgumentException(); } return result; }
Object value = classes.get(i); String category = ValueUtil.formatValue(value); labelCategories.add(ValueUtil.formatValue(negLabel)); labelCategories.add(ValueUtil.formatValue(posLabel)); Object value = classes.get(i); String category = ValueUtil.formatValue(value);
mapValues.setDefaultValue(ValueUtil.formatValue(defaultValue));
.setScore(ValueUtil.formatValue(classes.get(index))); ScoreDistribution scoreDistribution = new ScoreDistribution(ValueUtil.formatValue(classes.get(i)), probabilities[i]);
String value = ValueUtil.formatValue(splitValue.get(index));
static public Feature encodeFeature(Feature feature, Object replacementValue, MissingValueTreatmentMethod missingValueTreatmentMethod){ ModelEncoder encoder = (ModelEncoder)feature.getEncoder(); Field<?> field = feature.getField(); if(field instanceof DataField){ MissingValueDecorator missingValueDecorator = new MissingValueDecorator() .setMissingValueReplacement(ValueUtil.formatValue(replacementValue)) .setMissingValueTreatment(missingValueTreatmentMethod); encoder.addDecorator(feature.getName(), missingValueDecorator); return feature; } else { throw new IllegalArgumentException(); } } }
value = ValueUtil.formatValue(splitValue);
String value = ValueUtil.formatValue(splitValue);
private void encodeNode(org.dmg.pmml.tree.Node parent, int index, Schema schema){ parent.setId(String.valueOf(index + 1)); Node node = allNodes.get(index); if(!node.isLeaf()){ int splitIndex = node.getFeatureIndex(); Feature feature = schema.getFeature(splitIndex); org.dmg.pmml.tree.Node leftChild = new org.dmg.pmml.tree.Node() .setPredicate(encodePredicate(feature, node, true)); encodeNode(leftChild, node.getLeftChild().getId(), schema); org.dmg.pmml.tree.Node rightChild = new org.dmg.pmml.tree.Node() .setPredicate(encodePredicate(feature, node, false)); encodeNode(rightChild, node.getRightChild().getId(), schema); parent.addNodes(leftChild, rightChild); boolean defaultLeft = false; parent.setDefaultChild(defaultLeft ? leftChild.getId() : rightChild.getId()); } else { float value = (float)node.getValue(); parent.setScore(ValueUtil.formatValue(value)); } }
featureMap.addMissingValue(ValueUtil.formatValue(missing.asScalar()));