Examples with DerivedField org.dmg.pmml.DerivedField used on opensource projects

Example 26 with DerivedField

use of org.dmg.pmml.DerivedField in project shifu by ShifuML.

the class ZscoreLocalTransformCreator method build.

@Override
public LocalTransformations build(BasicML basicML) {
    LocalTransformations localTransformations = new LocalTransformations();
    if (basicML instanceof BasicFloatNetwork) {
        BasicFloatNetwork bfn = (BasicFloatNetwork) basicML;
        Set<Integer> featureSet = bfn.getFeatureSet();
        for (ColumnConfig config : columnConfigList) {
            if (config.isFinalSelect() && (CollectionUtils.isEmpty(featureSet) || featureSet.contains(config.getColumnNum()))) {
                double cutoff = modelConfig.getNormalizeStdDevCutOff();
                List<DerivedField> deriviedFields = config.isCategorical() ? createCategoricalDerivedField(config, cutoff, modelConfig.getNormalizeType()) : createNumericalDerivedField(config, cutoff, modelConfig.getNormalizeType());
                localTransformations.addDerivedFields(deriviedFields.toArray(new DerivedField[deriviedFields.size()]));
            }
        }
    } else {
        for (ColumnConfig config : columnConfigList) {
            if (config.isFinalSelect()) {
                double cutoff = modelConfig.getNormalizeStdDevCutOff();
                List<DerivedField> deriviedFields = config.isCategorical() ? createCategoricalDerivedField(config, cutoff, modelConfig.getNormalizeType()) : createNumericalDerivedField(config, cutoff, modelConfig.getNormalizeType());
                localTransformations.addDerivedFields(deriviedFields.toArray(new DerivedField[deriviedFields.size()]));
            }
        }
    }
    return localTransformations;
}

Example 27 with DerivedField

use of org.dmg.pmml.DerivedField in project shifu by ShifuML.

the class NeuralNetworkModelIntegrator method getNeuralInputs.

private NeuralInputs getNeuralInputs(final NeuralNetwork model) {
    NeuralInputs nnInputs = new NeuralInputs();
    // get HashMap for local transform and MiningSchema fields
    HashMap<FieldName, FieldName> reversMiningTransformMap = new HashMap<FieldName, FieldName>();
    HashMap<FieldName, List<FieldName>> treeMapOfTransform = new HashMap<FieldName, List<FieldName>>();
    for (DerivedField dField : model.getLocalTransformations().getDerivedFields()) {
        // Apply z-scale normalization on numerical variables
        FieldName parentField = null;
        if (dField.getExpression() instanceof NormContinuous) {
            parentField = ((NormContinuous) dField.getExpression()).getField();
            reversMiningTransformMap.put(dField.getName(), parentField);
        } else // Apply bin map on categorical variables
        if (dField.getExpression() instanceof MapValues) {
            parentField = ((MapValues) dField.getExpression()).getFieldColumnPairs().get(0).getField();
            reversMiningTransformMap.put(dField.getName(), parentField);
        } else if (dField.getExpression() instanceof Discretize) {
            parentField = ((Discretize) dField.getExpression()).getField();
            reversMiningTransformMap.put(dField.getName(), parentField);
        }
        List<FieldName> fieldNames = treeMapOfTransform.get(parentField);
        if (fieldNames == null) {
            fieldNames = new ArrayList<FieldName>();
        }
        fieldNames.add(dField.getName());
        treeMapOfTransform.put(parentField, fieldNames);
    }
    // comment here
    List<MiningField> miningList = model.getMiningSchema().getMiningFields();
    int index = 0;
    for (DerivedField dField : model.getLocalTransformations().getDerivedFields()) {
        List<FieldName> list = treeMapOfTransform.get(dField.getName());
        boolean isLeaf = (list == null || list.size() == 0);
        FieldName root = getRoot(dField.getName(), reversMiningTransformMap);
        if (isLeaf && isRootInMiningList(root, miningList)) {
            DerivedField field = new DerivedField(OpType.CONTINUOUS, DataType.DOUBLE).setName(dField.getName()).setExpression(new FieldRef(dField.getName()));
            nnInputs.addNeuralInputs(new NeuralInput("0," + (index++), field));
        }
    }
    DerivedField field = new DerivedField(OpType.CONTINUOUS, DataType.DOUBLE).setName(new FieldName(PluginConstants.biasValue)).setExpression(new FieldRef(new FieldName(PluginConstants.biasValue)));
    nnInputs.addNeuralInputs(new NeuralInput(PluginConstants.biasValue, field));
    return nnInputs;
}