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Example 1 with NeuralInput

use of org.dmg.pmml.neural_network.NeuralInput 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;
}
Also used : NormContinuous(org.dmg.pmml.NormContinuous) MiningField(org.dmg.pmml.MiningField) FieldRef(org.dmg.pmml.FieldRef) NeuralInputs(org.dmg.pmml.neural_network.NeuralInputs) HashMap(java.util.HashMap) MapValues(org.dmg.pmml.MapValues) Discretize(org.dmg.pmml.Discretize) ArrayList(java.util.ArrayList) List(java.util.List) FieldName(org.dmg.pmml.FieldName) DerivedField(org.dmg.pmml.DerivedField) NeuralInput(org.dmg.pmml.neural_network.NeuralInput)

Aggregations

ArrayList (java.util.ArrayList)1 HashMap (java.util.HashMap)1 List (java.util.List)1 DerivedField (org.dmg.pmml.DerivedField)1 Discretize (org.dmg.pmml.Discretize)1 FieldName (org.dmg.pmml.FieldName)1 FieldRef (org.dmg.pmml.FieldRef)1 MapValues (org.dmg.pmml.MapValues)1 MiningField (org.dmg.pmml.MiningField)1 NormContinuous (org.dmg.pmml.NormContinuous)1 NeuralInput (org.dmg.pmml.neural_network.NeuralInput)1 NeuralInputs (org.dmg.pmml.neural_network.NeuralInputs)1