Examples with TreeModel org.dmg.pmml.TreeModelDocument.TreeModel used on opensource projects

Example 1 with TreeModel

use of org.dmg.pmml.TreeModelDocument.TreeModel in project knime-core by knime.

the class AbstractGBTModelExporter method writeTreeIntoSegment.

private void writeTreeIntoSegment(final Segment segment, final TreeModelRegression tree, final Map<TreeNodeSignature, Double> coefficientMap) {
    assert m_pmmlSpec != null : "The pmml spec is null, this indicates an implementation mistake.";
    GBTRegressionTreeModelExporter exporter = new GBTRegressionTreeModelExporter(tree, m_derivedFieldMapper, coefficientMap);
    if (exporter.hasWarning()) {
        addWarning(exporter.getWarning());
    }
    TreeModel treeModel = segment.addNewTreeModel();
    exporter.writeModelToPMML(treeModel, m_pmmlSpec);
}

Example 2 with TreeModel

use of org.dmg.pmml.TreeModelDocument.TreeModel in project knime-core by knime.

the class AbstractTreeModelPMMLTranslator method initializeFrom.

/**
 * {@inheritDoc}
 */
@Override
public void initializeFrom(final PMMLDocument pmmlDoc) {
    PMML pmml = pmmlDoc.getPMML();
    List<TreeModel> trees = pmml.getTreeModelList();
    if (trees.size() > 1) {
        throw new IllegalArgumentException("This translator handles only single trees.");
    } else if (trees.isEmpty()) {
        throw new IllegalArgumentException("The provided PMMLDocument contains no tree models.");
    }
    MetaDataMapper<T> metaDataMapper = createMetaDataMapper(pmmlDoc, getTargetName(pmml));
    TreeModelImporter<N, M, T> importer = createImporter(metaDataMapper);
    m_treeModel = importer.importFromPMML(trees.get(0));
    m_treeMetaData = metaDataMapper.getTreeMetaData();
    m_learnSpec = metaDataMapper.getLearnSpec();
}

Example 3 with TreeModel

use of org.dmg.pmml.TreeModelDocument.TreeModel in project knime-core by knime.

the class AbstractTreeModelPMMLTranslator method exportTo.

/**
 * {@inheritDoc}
 */
@Override
public SchemaType exportTo(final PMMLDocument pmmlDoc, final PMMLPortObjectSpec spec) {
    PMML pmml = pmmlDoc.getPMML();
    TreeModelDocument.TreeModel treeModel = pmml.addNewTreeModel();
    AbstractTreeModelExporter<N> exporter = createExporter(new DerivedFieldMapper(pmmlDoc));
    SchemaType st = exporter.writeModelToPMML(treeModel, spec);
    if (exporter.hasWarning()) {
        addWarning(exporter.getWarning());
    }
    return st;
}

Example 4 with TreeModel

use of org.dmg.pmml.TreeModelDocument.TreeModel in project knime-core by knime.

the class PMMLPortObject method moveGlobalTransformationsToModel.

/**
 * Moves the content of the transformation dictionary to local
 * transformations of the model if a model exists.
 */
public void moveGlobalTransformationsToModel() {
    PMML pmml = m_pmmlDoc.getPMML();
    TransformationDictionary transDict = pmml.getTransformationDictionary();
    if (transDict == null || transDict.getDerivedFieldArray() == null || transDict.getDerivedFieldArray().length == 0) {
        // nothing to be moved
        return;
    }
    DerivedField[] globalDerivedFields = transDict.getDerivedFieldArray();
    LocalTransformations localTrans = null;
    if (pmml.getTreeModelArray().length > 0) {
        TreeModel model = pmml.getTreeModelArray(0);
        localTrans = model.getLocalTransformations();
        if (localTrans == null) {
            localTrans = model.addNewLocalTransformations();
        }
    } else if (pmml.getClusteringModelArray().length > 0) {
        ClusteringModel model = pmml.getClusteringModelArray(0);
        localTrans = model.getLocalTransformations();
        if (localTrans == null) {
            localTrans = model.addNewLocalTransformations();
        }
    } else if (pmml.getNeuralNetworkArray().length > 0) {
        NeuralNetwork model = pmml.getNeuralNetworkArray(0);
        localTrans = model.getLocalTransformations();
        if (localTrans == null) {
            localTrans = model.addNewLocalTransformations();
        }
    } else if (pmml.getSupportVectorMachineModelArray().length > 0) {
        SupportVectorMachineModel model = pmml.getSupportVectorMachineModelArray(0);
        localTrans = model.getLocalTransformations();
        if (localTrans == null) {
            localTrans = model.addNewLocalTransformations();
        }
    } else if (pmml.getRegressionModelArray().length > 0) {
        RegressionModel model = pmml.getRegressionModelArray(0);
        localTrans = model.getLocalTransformations();
        if (localTrans == null) {
            localTrans = model.addNewLocalTransformations();
        }
    } else if (pmml.getGeneralRegressionModelArray().length > 0) {
        GeneralRegressionModel model = pmml.getGeneralRegressionModelArray(0);
        localTrans = model.getLocalTransformations();
        if (localTrans == null) {
            localTrans = model.addNewLocalTransformations();
        }
    } else if (pmml.sizeOfRuleSetModelArray() > 0) {
        RuleSetModel model = pmml.getRuleSetModelArray(0);
        localTrans = model.getLocalTransformations();
        if (localTrans == null) {
            localTrans = model.addNewLocalTransformations();
        }
    }
    if (localTrans != null) {
        DerivedField[] derivedFields = appendDerivedFields(localTrans.getDerivedFieldArray(), globalDerivedFields);
        localTrans.setDerivedFieldArray(derivedFields);
        // remove derived fields from TransformationDictionary
        transDict.setDerivedFieldArray(new DerivedField[0]);
    }
// else do nothing as no model exists yet
}

Example 5 with TreeModel

use of org.dmg.pmml.TreeModelDocument.TreeModel in project knime-core by knime.

the class PMMLModelWrapper method getSegmentContent.

/**
 * Returns the content of a segment as a model wrapper.
 * @param s The segment
 * @return Returns a wrapper around the model
 */
public static PMMLModelWrapper getSegmentContent(final Segment s) {
    TreeModel treemodel = s.getTreeModel();
    if (treemodel != null) {
        return new PMMLTreeModelWrapper(treemodel);
    }
    RegressionModel regrmodel = s.getRegressionModel();
    if (regrmodel != null) {
        return new PMMLRegressionModelWrapper(regrmodel);
    }
    GeneralRegressionModel genregrmodel = s.getGeneralRegressionModel();
    if (genregrmodel != null) {
        return new PMMLGeneralRegressionModelWrapper(genregrmodel);
    }
    ClusteringModel clustmodel = s.getClusteringModel();
    if (clustmodel != null) {
        return new PMMLClusteringModelWrapper(clustmodel);
    }
    NaiveBayesModel nbmodel = s.getNaiveBayesModel();
    if (nbmodel != null) {
        return new PMMLNaiveBayesModelWrapper(nbmodel);
    }
    NeuralNetwork nn = s.getNeuralNetwork();
    if (nn != null) {
        return new PMMLNeuralNetworkWrapper(nn);
    }
    RuleSetModel rsmodel = s.getRuleSetModel();
    if (rsmodel != null) {
        return new PMMLRuleSetModelWrapper(rsmodel);
    }
    SupportVectorMachineModel svmmodel = s.getSupportVectorMachineModel();
    if (svmmodel != null) {
        return new PMMLSupportVectorMachineModelWrapper(svmmodel);
    }
    return null;
}