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

Example 21 with Feature

use of org.jpmml.converter.Feature 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 22 with Feature

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

the class RFormulaModelConverter method registerFeatures.

@Override
public void registerFeatures(SparkMLEncoder encoder) {
    RFormulaModel transformer = getTransformer();
    ResolvedRFormula resolvedFormula = transformer.resolvedFormula();
    String targetCol = resolvedFormula.label();
    String labelCol = transformer.getLabelCol();
    if (!(targetCol).equals(labelCol)) {
        List<Feature> features = encoder.getFeatures(targetCol);
        encoder.putFeatures(labelCol, features);
    }
    PipelineModel pipelineModel = transformer.pipelineModel();
    Transformer[] stages = pipelineModel.stages();
    for (Transformer stage : stages) {
        FeatureConverter<?> featureConverter = ConverterUtil.createFeatureConverter(stage);
        featureConverter.registerFeatures(encoder);
    }
}

Example 23 with Feature

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

the class RegexTokenizerConverter method encodeFeatures.

@Override
public List<Feature> encodeFeatures(SparkMLEncoder encoder) {
    RegexTokenizer transformer = getTransformer();
    if (!transformer.getGaps()) {
        throw new IllegalArgumentException("Expected splitter mode, got token matching mode");
    }
    if (transformer.getMinTokenLength() != 1) {
        throw new IllegalArgumentException("Expected 1 as minimum token length, got " + transformer.getMinTokenLength() + " as minimum token length");
    }
    Feature feature = encoder.getOnlyFeature(transformer.getInputCol());
    Field<?> field = encoder.getField(feature.getName());
    if (transformer.getToLowercase()) {
        Apply apply = PMMLUtil.createApply("lowercase", feature.ref());
        field = encoder.createDerivedField(FeatureUtil.createName("lowercase", feature), OpType.CATEGORICAL, DataType.STRING, apply);
    }
    return Collections.<Feature>singletonList(new DocumentFeature(encoder, field, transformer.getPattern()));
}

Example 24 with Feature

use of org.jpmml.converter.Feature 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 25 with Feature

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

the class ClusteringModelConverter method registerOutputFields.

@Override
public List<OutputField> registerOutputFields(Label label, SparkMLEncoder encoder) {
    T model = getTransformer();
    String predictionCol = model.getPredictionCol();
    OutputField predictedField = ModelUtil.createPredictedField(FieldName.create(predictionCol), DataType.STRING, OpType.CATEGORICAL);
    Feature feature = new Feature(encoder, predictedField.getName(), predictedField.getDataType()) {

        @Override
        public ContinuousFeature toContinuousFeature() {
            throw new UnsupportedOperationException();
        }
    };
    encoder.putOnlyFeature(predictionCol, feature);
    return Collections.singletonList(predictedField);
}