本文整理汇总了Java中org.dmg.pmml.tree.Node.addNodes方法的典型用法代码示例。如果您正苦于以下问题:Java Node.addNodes方法的具体用法?Java Node.addNodes怎么用?Java Node.addNodes使用的例子?那么恭喜您, 这里精选的方法代码示例或许可以为您提供帮助。您也可以进一步了解该方法所在类org.dmg.pmml.tree.Node
的用法示例。
在下文中一共展示了Node.addNodes方法的8个代码示例,这些例子默认根据受欢迎程度排序。您可以为喜欢或者感觉有用的代码点赞,您的评价将有助于系统推荐出更棒的Java代码示例。
示例1: buildDummyClassificationModel
import org.dmg.pmml.tree.Node; //导入方法依赖的package包/类
private static PMML buildDummyClassificationModel(int numTrees) {
PMML pmml = PMMLUtils.buildSkeletonPMML();
List<DataField> dataFields = new ArrayList<>();
DataField predictor =
new DataField(FieldName.create("color"), OpType.CATEGORICAL, DataType.STRING);
predictor.addValues(new Value("yellow"), new Value("red"));
dataFields.add(predictor);
DataField target =
new DataField(FieldName.create("fruit"), OpType.CATEGORICAL, DataType.STRING);
target.addValues(new Value("banana"), new Value("apple"));
dataFields.add(target);
DataDictionary dataDictionary =
new DataDictionary(dataFields).setNumberOfFields(dataFields.size());
pmml.setDataDictionary(dataDictionary);
List<MiningField> miningFields = new ArrayList<>();
MiningField predictorMF = new MiningField(FieldName.create("color"))
.setOpType(OpType.CATEGORICAL)
.setUsageType(MiningField.UsageType.ACTIVE)
.setImportance(0.5);
miningFields.add(predictorMF);
MiningField targetMF = new MiningField(FieldName.create("fruit"))
.setOpType(OpType.CATEGORICAL)
.setUsageType(MiningField.UsageType.PREDICTED);
miningFields.add(targetMF);
MiningSchema miningSchema = new MiningSchema(miningFields);
double dummyCount = 2.0;
Node rootNode = new Node().setId("r").setRecordCount(dummyCount).setPredicate(new True());
double halfCount = dummyCount / 2;
Node left = new Node().setId("r-").setRecordCount(halfCount).setPredicate(new True());
left.addScoreDistributions(new ScoreDistribution("apple", halfCount));
Node right = new Node().setId("r+").setRecordCount(halfCount)
.setPredicate(new SimpleSetPredicate(FieldName.create("color"),
SimpleSetPredicate.BooleanOperator.IS_NOT_IN,
new Array(Array.Type.STRING, "red")));
right.addScoreDistributions(new ScoreDistribution("banana", halfCount));
rootNode.addNodes(right, left);
TreeModel treeModel = new TreeModel(MiningFunction.CLASSIFICATION, miningSchema, rootNode)
.setSplitCharacteristic(TreeModel.SplitCharacteristic.BINARY_SPLIT)
.setMissingValueStrategy(TreeModel.MissingValueStrategy.DEFAULT_CHILD);
if (numTrees > 1) {
MiningModel miningModel = new MiningModel(MiningFunction.CLASSIFICATION, miningSchema);
List<Segment> segments = new ArrayList<>();
for (int i = 0; i < numTrees; i++) {
segments.add(new Segment()
.setId(Integer.toString(i))
.setPredicate(new True())
.setModel(treeModel)
.setWeight(1.0));
}
miningModel.setSegmentation(
new Segmentation(Segmentation.MultipleModelMethod.WEIGHTED_MAJORITY_VOTE, segments));
pmml.addModels(miningModel);
} else {
pmml.addModels(treeModel);
}
return pmml;
}
示例2: buildDummyRegressionModel
import org.dmg.pmml.tree.Node; //导入方法依赖的package包/类
public static PMML buildDummyRegressionModel() {
PMML pmml = PMMLUtils.buildSkeletonPMML();
List<DataField> dataFields = new ArrayList<>();
dataFields.add(new DataField(FieldName.create("foo"), OpType.CONTINUOUS, DataType.DOUBLE));
dataFields.add(new DataField(FieldName.create("bar"), OpType.CONTINUOUS, DataType.DOUBLE));
DataDictionary dataDictionary =
new DataDictionary(dataFields).setNumberOfFields(dataFields.size());
pmml.setDataDictionary(dataDictionary);
List<MiningField> miningFields = new ArrayList<>();
MiningField predictorMF = new MiningField(FieldName.create("foo"))
.setOpType(OpType.CONTINUOUS)
.setUsageType(MiningField.UsageType.ACTIVE)
.setImportance(0.5);
miningFields.add(predictorMF);
MiningField targetMF = new MiningField(FieldName.create("bar"))
.setOpType(OpType.CONTINUOUS)
.setUsageType(MiningField.UsageType.PREDICTED);
miningFields.add(targetMF);
MiningSchema miningSchema = new MiningSchema(miningFields);
double dummyCount = 2.0;
Node rootNode = new Node().setId("r").setRecordCount(dummyCount).setPredicate(new True());
double halfCount = dummyCount / 2;
Node left = new Node()
.setId("r-")
.setRecordCount(halfCount)
.setPredicate(new True())
.setScore("-2.0");
Node right = new Node().setId("r+").setRecordCount(halfCount)
.setPredicate(new SimplePredicate(FieldName.create("foo"),
SimplePredicate.Operator.GREATER_THAN).setValue("3.14"))
.setScore("2.0");
rootNode.addNodes(right, left);
TreeModel treeModel = new TreeModel(MiningFunction.REGRESSION, miningSchema, rootNode)
.setSplitCharacteristic(TreeModel.SplitCharacteristic.BINARY_SPLIT)
.setMissingValueStrategy(TreeModel.MissingValueStrategy.DEFAULT_CHILD)
.setMiningSchema(miningSchema);
pmml.addModels(treeModel);
return pmml;
}
示例3: encodeNode
import org.dmg.pmml.tree.Node; //导入方法依赖的package包/类
private void encodeNode(Node node, RGenericVector tree, Schema schema){
RIntegerVector nodeId = (RIntegerVector)tree.getValue("nodeID");
RBooleanVector terminal = (RBooleanVector)tree.getValue("terminal");
RGenericVector psplit = (RGenericVector)tree.getValue("psplit");
RGenericVector ssplits = (RGenericVector)tree.getValue("ssplits");
RDoubleVector prediction = (RDoubleVector)tree.getValue("prediction");
RGenericVector left = (RGenericVector)tree.getValue("left");
RGenericVector right = (RGenericVector)tree.getValue("right");
node.setId(String.valueOf(nodeId.asScalar()));
if((Boolean.TRUE).equals(terminal.asScalar())){
node = encodeScore(node, prediction, schema);
return;
}
RNumberVector<?> splitpoint = (RNumberVector<?>)psplit.getValue("splitpoint");
RStringVector variableName = (RStringVector)psplit.getValue("variableName");
if(ssplits.size() > 0){
throw new IllegalArgumentException();
}
Predicate leftPredicate;
Predicate rightPredicate;
FieldName name = FieldName.create(variableName.asScalar());
Integer index = this.featureIndexes.get(name);
if(index == null){
throw new IllegalArgumentException();
}
Feature feature = schema.getFeature(index);
if(feature instanceof CategoricalFeature){
CategoricalFeature categoricalFeature = (CategoricalFeature)feature;
List<String> values = categoricalFeature.getValues();
List<Integer> splitValues = (List<Integer>)splitpoint.getValues();
leftPredicate = createSimpleSetPredicate(categoricalFeature, selectValues(values, splitValues, true));
rightPredicate = createSimpleSetPredicate(categoricalFeature, selectValues(values, splitValues, false));
} else
{
ContinuousFeature continuousFeature = feature.toContinuousFeature();
String value = ValueUtil.formatValue((Double)splitpoint.asScalar());
leftPredicate = createSimplePredicate(continuousFeature, SimplePredicate.Operator.LESS_OR_EQUAL, value);
rightPredicate = createSimplePredicate(continuousFeature, SimplePredicate.Operator.GREATER_THAN, value);
}
Node leftChild = new Node()
.setPredicate(leftPredicate);
encodeNode(leftChild, left, schema);
Node rightChild = new Node()
.setPredicate(rightPredicate);
encodeNode(rightChild, right, schema);
node.addNodes(leftChild, rightChild);
}
示例4: encodeNode
import org.dmg.pmml.tree.Node; //导入方法依赖的package包/类
private <P extends Number> void encodeNode(Node node, int i, ScoreEncoder<P> scoreEncoder, List<? extends Number> leftDaughter, List<? extends Number> rightDaughter, List<? extends Number> bestvar, List<Double> xbestsplit, List<P> nodepred, Schema schema){
Predicate leftPredicate;
Predicate rightPredicate;
int var = ValueUtil.asInt(bestvar.get(i));
if(var != 0){
Feature feature = schema.getFeature(var - 1);
Double split = xbestsplit.get(i);
if(feature instanceof BooleanFeature){
BooleanFeature booleanFeature = (BooleanFeature)feature;
if(split != 0.5d){
throw new IllegalArgumentException();
}
leftPredicate = createSimplePredicate(booleanFeature, SimplePredicate.Operator.EQUAL, booleanFeature.getValue(0));
rightPredicate = createSimplePredicate(booleanFeature, SimplePredicate.Operator.EQUAL, booleanFeature.getValue(1));
} else
if(feature instanceof CategoricalFeature){
CategoricalFeature categoricalFeature = (CategoricalFeature)feature;
List<String> values = categoricalFeature.getValues();
leftPredicate = createSimpleSetPredicate(categoricalFeature, selectValues(values, split, true));
rightPredicate = createSimpleSetPredicate(categoricalFeature, selectValues(values, split, false));
} else
{
ContinuousFeature continuousFeature = feature.toContinuousFeature();
String value = ValueUtil.formatValue(split);
leftPredicate = createSimplePredicate(continuousFeature, SimplePredicate.Operator.LESS_OR_EQUAL, value);
rightPredicate = createSimplePredicate(continuousFeature, SimplePredicate.Operator.GREATER_THAN, value);
}
} else
{
P prediction = nodepred.get(i);
node.setScore(scoreEncoder.encode(prediction));
return;
}
int left = ValueUtil.asInt(leftDaughter.get(i));
if(left != 0){
Node leftChild = new Node()
.setId(String.valueOf(left))
.setPredicate(leftPredicate);
encodeNode(leftChild, left - 1, scoreEncoder, leftDaughter, rightDaughter, bestvar, xbestsplit, nodepred, schema);
node.addNodes(leftChild);
}
int right = ValueUtil.asInt(rightDaughter.get(i));
if(right != 0){
Node rightChild = new Node()
.setId(String.valueOf(right))
.setPredicate(rightPredicate);
encodeNode(rightChild, right - 1, scoreEncoder, leftDaughter, rightDaughter, bestvar, xbestsplit, nodepred, schema);
node.addNodes(rightChild);
}
}
示例5: transform
import org.dmg.pmml.tree.Node; //导入方法依赖的package包/类
@Test
public void transform(){
Node node1a = new Node();
Node node2a = new Node();
Node node2b = new Node();
node1a.addNodes(node2a, node2b);
Node node3a = new Node();
node2a.addNodes(node3a);
assertTrue(node1a.getNodes() instanceof ArrayList);
assertTrue(node2a.getNodes() instanceof ArrayList);
TreeModel treeModel = new TreeModel(MiningFunction.CLASSIFICATION, new MiningSchema(), node1a);
ArrayListTransformer transformer = new ArrayListTransformer();
transformer.applyTo(treeModel);
assertTrue(node1a.getNodes() instanceof DoubletonList);
assertTrue(node2a.getNodes() instanceof SingletonList);
}
示例6: find
import org.dmg.pmml.tree.Node; //导入方法依赖的package包/类
@Test
public void find(){
Node node1a = new Node();
Node node2a = new Node();
Node node2b = new Node();
Node node2c = new Node();
node1a.addNodes(node2a, node2b, node2c);
Node node3a = new Node();
Node node3b = new Node();
node2b.addNodes(node3a);
node2c.addNodes(node3b);
Node node4a = new Node();
node3a.addNodes(node4a);
TreeModel treeModel = new TreeModel(MiningFunction.CLASSIFICATION, new MiningSchema(), node1a);
TreePathFinder finder = new TreePathFinder();
finder.applyTo(treeModel);
Map<Node, List<Node>> paths = finder.getPaths();
assertEquals(3, paths.size());
assertEquals(Arrays.asList(node1a, node2a), paths.get(node2a));
assertEquals(Arrays.asList(node1a, node2b, node3a, node4a), paths.get(node4a));
assertEquals(Arrays.asList(node1a, node2c, node3b), paths.get(node3b));
}
示例7: encodeNode
import org.dmg.pmml.tree.Node; //导入方法依赖的package包/类
private void encodeNode(Node node, int index, ScoreEncoder scoreEncoder, RNumberVector<?> leftChildIDs, RNumberVector<?> rightChildIDs, RNumberVector<?> splitVarIDs, RNumberVector<?> splitValues, RGenericVector terminalClassCounts, Schema schema){
int leftIndex = ValueUtil.asInt(leftChildIDs.getValue(index));
int rightIndex = ValueUtil.asInt(rightChildIDs.getValue(index));
Number splitValue = splitValues.getValue(index);
RNumberVector<?> terminalClassCount = (terminalClassCounts != null ? (RNumberVector<?>)terminalClassCounts.getValue(index) : null);
if(leftIndex == 0 && rightIndex == 0){
scoreEncoder.encode(node, splitValue, terminalClassCount);
return;
}
Predicate leftPredicate;
Predicate rightPredicate;
int splitVarIndex = ValueUtil.asInt(splitVarIDs.getValue(index));
Feature feature = schema.getFeature(splitVarIndex - 1);
if(feature instanceof CategoricalFeature){
CategoricalFeature categoricalFeature = (CategoricalFeature)feature;
int splitLevelIndex = ValueUtil.asInt(Math.floor(splitValue.doubleValue()));
List<String> values = categoricalFeature.getValues();
leftPredicate = createSimpleSetPredicate(categoricalFeature, values.subList(0, splitLevelIndex));
rightPredicate = createSimpleSetPredicate(categoricalFeature, values.subList(splitLevelIndex, values.size()));
} else
{
ContinuousFeature continuousFeature = feature.toContinuousFeature();
String value = ValueUtil.formatValue(splitValue);
leftPredicate = createSimplePredicate(continuousFeature, SimplePredicate.Operator.LESS_OR_EQUAL, value);
rightPredicate = createSimplePredicate(continuousFeature, SimplePredicate.Operator.GREATER_THAN, value);
}
Node leftChild = new Node()
.setPredicate(leftPredicate);
encodeNode(leftChild, leftIndex, scoreEncoder, leftChildIDs, rightChildIDs, splitVarIDs, splitValues, terminalClassCounts, schema);
Node rightChild = new Node()
.setPredicate(rightPredicate);
encodeNode(rightChild, rightIndex, scoreEncoder, leftChildIDs, rightChildIDs, splitVarIDs, splitValues, terminalClassCounts, schema);
node.addNodes(leftChild, rightChild);
}
示例8: encodeNode
import org.dmg.pmml.tree.Node; //导入方法依赖的package包/类
private void encodeNode(Node node, int index, int depth, List<Integer> nodeStatus, List<Integer> nodeSize, List<Integer> leftDaughter, List<Integer> rightDaughter, List<Integer> splitAtt, List<Double> splitValue, Schema schema){
int status = nodeStatus.get(index);
int size = nodeSize.get(index);
node.setId(String.valueOf(index + 1));
// Interior node
if(status == -3){
int att = splitAtt.get(index);
ContinuousFeature feature = (ContinuousFeature)schema.getFeature(att - 1);
String value = ValueUtil.formatValue(splitValue.get(index));
Predicate leftPredicate = createSimplePredicate(feature, SimplePredicate.Operator.LESS_THAN, value);
Node leftChild = new Node()
.setPredicate(leftPredicate);
int leftIndex = (leftDaughter.get(index) - 1);
encodeNode(leftChild, leftIndex, depth + 1, nodeStatus, nodeSize, leftDaughter, rightDaughter, splitAtt, splitValue, schema);
Predicate rightPredicate = createSimplePredicate(feature, SimplePredicate.Operator.GREATER_OR_EQUAL, value);
Node rightChild = new Node()
.setPredicate(rightPredicate);
int rightIndex = (rightDaughter.get(index) - 1);
encodeNode(rightChild, rightIndex, depth + 1, nodeStatus, nodeSize, leftDaughter, rightDaughter, splitAtt, splitValue, schema);
node.addNodes(leftChild, rightChild);
} else
// Terminal node
if(status == -1){
node.setScore(ValueUtil.formatValue(depth + avgPathLength(size)));
} else
{
throw new IllegalArgumentException();
}
}