Examples with CategoricalFeature org.jpmml.converter.CategoricalFeature used on opensource projects

Example 6 with CategoricalFeature

use of org.jpmml.converter.CategoricalFeature in project jpmml-sparkml by jpmml.

the class OneHotEncoderModelConverter method encodeFeatures.

@Override
public List<Feature> encodeFeatures(SparkMLEncoder encoder) {
    OneHotEncoderModel transformer = getTransformer();
    String[] inputCols = transformer.getInputCols();
    boolean dropLast = transformer.getDropLast();
    List<Feature> result = new ArrayList<>();
    for (int i = 0; i < inputCols.length; i++) {
        CategoricalFeature categoricalFeature = (CategoricalFeature) encoder.getOnlyFeature(inputCols[i]);
        List<String> values = categoricalFeature.getValues();
        if (dropLast) {
            values = values.subList(0, values.size() - 1);
        }
        List<BinaryFeature> binaryFeatures = new ArrayList<>();
        for (String value : values) {
            binaryFeatures.add(new BinaryFeature(encoder, categoricalFeature.getName(), DataType.STRING, value));
        }
        result.add(new BinarizedCategoricalFeature(encoder, categoricalFeature.getName(), categoricalFeature.getDataType(), binaryFeatures));
    }
    return result;
}

Example 7 with CategoricalFeature

use of org.jpmml.converter.CategoricalFeature in project jpmml-sparkml by jpmml.

the class BinarizerConverter method encodeFeatures.

@Override
public List<Feature> encodeFeatures(SparkMLEncoder encoder) {
    Binarizer transformer = getTransformer();
    Feature feature = encoder.getOnlyFeature(transformer.getInputCol());
    ContinuousFeature continuousFeature = feature.toContinuousFeature();
    Apply apply = new Apply("if").addExpressions(PMMLUtil.createApply("lessOrEqual", continuousFeature.ref(), PMMLUtil.createConstant(transformer.getThreshold()))).addExpressions(PMMLUtil.createConstant(0d), PMMLUtil.createConstant(1d));
    DerivedField derivedField = encoder.createDerivedField(formatName(transformer), OpType.CATEGORICAL, DataType.DOUBLE, apply);
    return Collections.<Feature>singletonList(new CategoricalFeature(encoder, derivedField, Arrays.asList("0", "1")));
}

Example 8 with CategoricalFeature

use of org.jpmml.converter.CategoricalFeature in project jpmml-r by jpmml.

the class GBMConverter method encodeNode.

private void encodeNode(Node node, int i, RGenericVector tree, RGenericVector c_splits, Schema schema) {
    RIntegerVector splitVar = (RIntegerVector) tree.getValue(0);
    RDoubleVector splitCodePred = (RDoubleVector) tree.getValue(1);
    RIntegerVector leftNode = (RIntegerVector) tree.getValue(2);
    RIntegerVector rightNode = (RIntegerVector) tree.getValue(3);
    RIntegerVector missingNode = (RIntegerVector) tree.getValue(4);
    RDoubleVector prediction = (RDoubleVector) tree.getValue(7);
    Predicate missingPredicate;
    Predicate leftPredicate;
    Predicate rightPredicate;
    Integer var = splitVar.getValue(i);
    if (var != -1) {
        Feature feature = schema.getFeature(var);
        missingPredicate = createSimplePredicate(feature, SimplePredicate.Operator.IS_MISSING, null);
        Double split = splitCodePred.getValue(i);
        if (feature instanceof CategoricalFeature) {
            CategoricalFeature categoricalFeature = (CategoricalFeature) feature;
            List<String> values = categoricalFeature.getValues();
            int index = ValueUtil.asInt(split);
            RIntegerVector c_split = (RIntegerVector) c_splits.getValue(index);
            List<Integer> splitValues = c_split.getValues();
            leftPredicate = createSimpleSetPredicate(categoricalFeature, selectValues(values, splitValues, true));
            rightPredicate = createSimpleSetPredicate(categoricalFeature, selectValues(values, splitValues, false));
        } else {
            ContinuousFeature continuousFeature = feature.toContinuousFeature();
            String value = ValueUtil.formatValue(split);
            leftPredicate = createSimplePredicate(continuousFeature, SimplePredicate.Operator.LESS_THAN, value);
            rightPredicate = createSimplePredicate(continuousFeature, SimplePredicate.Operator.GREATER_OR_EQUAL, value);
        }
    } else {
        Double value = prediction.getValue(i);
        node.setScore(ValueUtil.formatValue(value));
        return;
    }
    Integer missing = missingNode.getValue(i);
    if (missing != -1) {
        Node missingChild = new Node().setId(String.valueOf(missing + 1)).setPredicate(missingPredicate);
        encodeNode(missingChild, missing, tree, c_splits, schema);
        node.addNodes(missingChild);
    }
    Integer left = leftNode.getValue(i);
    if (left != -1) {
        Node leftChild = new Node().setId(String.valueOf(left + 1)).setPredicate(leftPredicate);
        encodeNode(leftChild, left, tree, c_splits, schema);
        node.addNodes(leftChild);
    }
    Integer right = rightNode.getValue(i);
    if (right != -1) {
        Node rightChild = new Node().setId(String.valueOf(right + 1)).setPredicate(rightPredicate);
        encodeNode(rightChild, right, tree, c_splits, schema);
        node.addNodes(rightChild);
    }
}

Example 9 with CategoricalFeature

use of org.jpmml.converter.CategoricalFeature in project jpmml-r by jpmml.

the class BinaryTreeConverter method encodeNode.

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);
}

Example 10 with CategoricalFeature

use of org.jpmml.converter.CategoricalFeature in project jpmml-r by jpmml.

the class Formula method addField.

public void addField(Field<?> field, List<String> categoryNames, List<String> categoryValues) {
    RExpEncoder encoder = getEncoder();
    if (categoryNames.size() != categoryValues.size()) {
        throw new IllegalArgumentException();
    }
    CategoricalFeature categoricalFeature;
    if ((DataType.BOOLEAN).equals(field.getDataType()) && (categoryValues.size() == 2) && ("false").equals(categoryValues.get(0)) && ("true").equals(categoryValues.get(1))) {
        categoricalFeature = new BooleanFeature(encoder, field);
    } else {
        categoricalFeature = new CategoricalFeature(encoder, field, categoryValues);
    }
    putFeature(field.getName(), categoricalFeature);
    for (int i = 0; i < categoryNames.size(); i++) {
        String categoryName = categoryNames.get(i);
        String categoryValue = categoryValues.get(i);
        BinaryFeature binaryFeature = new BinaryFeature(encoder, field, categoryValue);
        putFeature(FieldName.create((field.getName()).getValue() + categoryName), binaryFeature);
    }
    this.fields.add(field);
}