Examples with TreeModelRegression org.knime.base.node.mine.treeensemble2.model.TreeModelRegression used on opensource projects

Example 11 with TreeModelRegression

use of org.knime.base.node.mine.treeensemble2.model.TreeModelRegression in project knime-core by knime.

the class AbstractGBTModelExporter method writeSumSegmentation.

protected void writeSumSegmentation(final Segmentation segmentation, final Collection<TreeModelRegression> trees, final Collection<Map<TreeNodeSignature, Double>> coefficientMaps) {
    assert trees.size() == coefficientMaps.size() : "The number of trees does not match the number of coefficient maps.";
    segmentation.setMultipleModelMethod(MULTIPLEMODELMETHOD.SUM);
    Iterator<TreeModelRegression> treeIterator = trees.iterator();
    Iterator<Map<TreeNodeSignature, Double>> coefficientMapIterator = coefficientMaps.iterator();
    for (int i = 1; i <= trees.size(); i++) {
        Segment segment = segmentation.addNewSegment();
        segment.setId(Integer.toString(i));
        segment.addNewTrue();
        writeTreeIntoSegment(segment, treeIterator.next(), coefficientMapIterator.next());
    }
}

Example 12 with TreeModelRegression

use of org.knime.base.node.mine.treeensemble2.model.TreeModelRegression in project knime-core by knime.

the class ClassificationGBTModelImporter method importFromPMMLInternal.

/**
 * {@inheritDoc}
 */
@Override
protected MultiClassGradientBoostedTreesModel importFromPMMLInternal(final MiningModel miningModel) {
    Segmentation modelChain = miningModel.getSegmentation();
    CheckUtils.checkArgument(modelChain.getMultipleModelMethod() == MULTIPLEMODELMETHOD.MODEL_CHAIN, "The top level segmentation should have multiple model method '%s' but has '%s'", MULTIPLEMODELMETHOD.MODEL_CHAIN, modelChain.getMultipleModelMethod());
    List<List<TreeModelRegression>> trees = new ArrayList<>();
    List<List<Map<TreeNodeSignature, Double>>> coefficientMaps = new ArrayList<>();
    List<String> classLabels = new ArrayList<>();
    List<Segment> segments = modelChain.getSegmentList();
    for (int i = 0; i < segments.size() - 1; i++) {
        Pair<List<TreeModelRegression>, List<Map<TreeNodeSignature, Double>>> gbtPair = processClassSegment(segments.get(i));
        trees.add(gbtPair.getFirst());
        coefficientMaps.add(gbtPair.getSecond());
        classLabels.add(extractClassLabel(segments.get(i)));
    }
    double initialValue = extractInitialValue(segments.get(0));
    return MultiClassGradientBoostedTreesModel.create(getMetaDataMapper().getTreeMetaData(), trees, coefficientMaps, initialValue, TreeType.Ordinary, classLabels);
}

Example 13 with TreeModelRegression

use of org.knime.base.node.mine.treeensemble2.model.TreeModelRegression in project knime-core by knime.

the class AbstractGBTModelImporter method readTreeModel.

private Pair<TreeModelRegression, Map<TreeNodeSignature, Double>> readTreeModel(final Segment segment) {
    GBTRegressionContentParser contentParser = new GBTRegressionContentParser();
    TreeModelImporter<TreeNodeRegression, TreeModelRegression, TreeTargetNumericColumnMetaData> treeImporter = new TreeModelImporter<TreeNodeRegression, TreeModelRegression, TreeTargetNumericColumnMetaData>(m_metaDataMapper, m_conditionParser, m_signatureFactory, contentParser, m_treeFactory);
    TreeModel treeModel = segment.getTreeModel();
    TreeModelRegression tree = treeImporter.importFromPMML(treeModel);
    Map<TreeNodeSignature, Double> coefficientMap = contentParser.getCoefficientMap();
    return new Pair<>(tree, coefficientMap);
}

Example 14 with TreeModelRegression

use of org.knime.base.node.mine.treeensemble2.model.TreeModelRegression in project knime-core by knime.

the class AbstractGBTModelImporter method readSumSegmentation.

protected Pair<List<TreeModelRegression>, List<Map<TreeNodeSignature, Double>>> readSumSegmentation(final Segmentation segmentation) {
    List<Segment> segments = segmentation.getSegmentList();
    List<TreeModelRegression> trees = new ArrayList<>(segments.size());
    List<Map<TreeNodeSignature, Double>> coefficientMaps = new ArrayList<>(segments.size());
    for (Segment segment : segments) {
        Pair<TreeModelRegression, Map<TreeNodeSignature, Double>> treeCoeffientMapPair = readTreeModel(segment);
        trees.add(treeCoeffientMapPair.getFirst());
        coefficientMaps.add(treeCoeffientMapPair.getSecond());
    }
    return new Pair<>(trees, coefficientMaps);
}

Example 15 with TreeModelRegression

use of org.knime.base.node.mine.treeensemble2.model.TreeModelRegression in project knime-core by knime.

the class ClassificationGBTModelExporter method addSegmentation.

private void addSegmentation(final MiningModel miningModel, final int c) {
    Segmentation seg = miningModel.addNewSegmentation();
    MultiClassGradientBoostedTreesModel gbt = getGBTModel();
    Collection<TreeModelRegression> trees = IntStream.range(0, gbt.getNrLevels()).mapToObj(i -> gbt.getModel(i, c)).collect(Collectors.toList());
    Collection<Map<TreeNodeSignature, Double>> coefficientMaps = IntStream.range(0, gbt.getNrLevels()).mapToObj(i -> gbt.getCoefficientMap(i, c)).collect(Collectors.toList());
    writeSumSegmentation(seg, trees, coefficientMaps);
}