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

Example 36 with Feature

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

the class RandomForestConverter method encodeFormula.

private void encodeFormula(RExpEncoder encoder) {
    RGenericVector randomForest = getObject();
    RGenericVector forest = (RGenericVector) randomForest.getValue("forest");
    RNumberVector<?> y = (RNumberVector<?>) randomForest.getValue("y", true);
    RExp terms = randomForest.getValue("terms");
    final RNumberVector<?> ncat = (RNumberVector<?>) forest.getValue("ncat");
    final RGenericVector xlevels = (RGenericVector) forest.getValue("xlevels");
    RIntegerVector response = (RIntegerVector) terms.getAttributeValue("response");
    FormulaContext context = new FormulaContext() {

        @Override
        public List<String> getCategories(String variable) {
            if (ncat != null && ncat.hasValue(variable)) {
                if ((ncat.getValue(variable)).doubleValue() > 1d) {
                    RStringVector levels = (RStringVector) xlevels.getValue(variable);
                    return levels.getValues();
                }
            }
            return null;
        }

        @Override
        public RGenericVector getData() {
            return null;
        }
    };
    Formula formula = FormulaUtil.createFormula(terms, context, encoder);
    // Dependent variable
    int responseIndex = response.asScalar();
    if (responseIndex != 0) {
        DataField dataField = (DataField) formula.getField(responseIndex - 1);
        if (y instanceof RIntegerVector) {
            dataField = (DataField) encoder.toCategorical(dataField.getName(), RExpUtil.getFactorLevels(y));
        }
        encoder.setLabel(dataField);
    } else {
        throw new IllegalArgumentException();
    }
    RStringVector xlevelNames = xlevels.names();
    // Independent variables
    for (int i = 0; i < xlevelNames.size(); i++) {
        String xlevelName = xlevelNames.getValue(i);
        Feature feature = formula.resolveFeature(FieldName.create(xlevelName));
        encoder.addFeature(feature);
    }
}

Example 37 with Feature

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

the class RExpEncoder method addFeature.

public void addFeature(Field<?> field) {
    Feature feature;
    OpType opType = field.getOpType();
    switch(opType) {
        case CATEGORICAL:
            feature = new CategoricalFeature(this, (DataField) field);
            break;
        case CONTINUOUS:
            feature = new ContinuousFeature(this, field);
            break;
        default:
            throw new IllegalArgumentException();
    }
    addFeature(feature);
}

Example 38 with Feature

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

the class ImputerModelConverter method encodeFeatures.

@Override
public List<Feature> encodeFeatures(SparkMLEncoder encoder) {
    ImputerModel transformer = getTransformer();
    Double missingValue = transformer.getMissingValue();
    String strategy = transformer.getStrategy();
    Dataset<Row> surrogateDF = transformer.surrogateDF();
    String[] inputCols = transformer.getInputCols();
    String[] outputCols = transformer.getOutputCols();
    if (inputCols.length != outputCols.length) {
        throw new IllegalArgumentException();
    }
    MissingValueTreatmentMethod missingValueTreatmentMethod = parseStrategy(strategy);
    List<Row> surrogateRows = surrogateDF.collectAsList();
    if (surrogateRows.size() != 1) {
        throw new IllegalArgumentException();
    }
    Row surrogateRow = surrogateRows.get(0);
    List<Feature> result = new ArrayList<>();
    for (int i = 0; i < inputCols.length; i++) {
        String inputCol = inputCols[i];
        String outputCol = outputCols[i];
        Feature feature = encoder.getOnlyFeature(inputCol);
        Field<?> field = encoder.getField(feature.getName());
        if (field instanceof DataField) {
            DataField dataField = (DataField) field;
            Object surrogate = surrogateRow.getAs(inputCol);
            MissingValueDecorator missingValueDecorator = new MissingValueDecorator().setMissingValueReplacement(ValueUtil.formatValue(surrogate)).setMissingValueTreatment(missingValueTreatmentMethod);
            if (missingValue != null && !missingValue.isNaN()) {
                missingValueDecorator.addValues(ValueUtil.formatValue(missingValue));
            }
            encoder.addDecorator(feature.getName(), missingValueDecorator);
        } else {
            throw new IllegalArgumentException();
        }
        result.add(feature);
    }
    return result;
}

Example 39 with Feature

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

the class IndexToStringConverter method encodeFeatures.

@Override
public List<Feature> encodeFeatures(SparkMLEncoder encoder) {
    IndexToString transformer = getTransformer();
    DataField dataField = encoder.createDataField(formatName(transformer), OpType.CATEGORICAL, DataType.STRING, Arrays.asList(transformer.getLabels()));
    return Collections.<Feature>singletonList(new CategoricalFeature(encoder, dataField));
}

Example 40 with Feature

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

the class MaxAbsScalerModelConverter method encodeFeatures.

@Override
public List<Feature> encodeFeatures(SparkMLEncoder encoder) {
    MaxAbsScalerModel transformer = getTransformer();
    List<Feature> features = encoder.getFeatures(transformer.getInputCol());
    Vector maxAbs = transformer.maxAbs();
    if (maxAbs.size() != features.size()) {
        throw new IllegalArgumentException();
    }
    List<Feature> result = new ArrayList<>();
    for (int i = 0; i < features.size(); i++) {
        Feature feature = features.get(i);
        double maxAbsUnzero = maxAbs.apply(i);
        if (maxAbsUnzero == 0d) {
            maxAbsUnzero = 1d;
        }
        if (!ValueUtil.isOne(maxAbsUnzero)) {
            ContinuousFeature continuousFeature = feature.toContinuousFeature();
            Expression expression = PMMLUtil.createApply("/", continuousFeature.ref(), PMMLUtil.createConstant(maxAbsUnzero));
            DerivedField derivedField = encoder.createDerivedField(formatName(transformer, i), OpType.CONTINUOUS, DataType.DOUBLE, expression);
            feature = new ContinuousFeature(encoder, derivedField);
        }
        result.add(feature);
    }
    return result;
}