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

Example 21 with Expression

use of org.dmg.pmml.Expression in project jpmml-sparkml by jpmml.

the class MinMaxScalerModelConverter method encodeFeatures.

@Override
public List<Feature> encodeFeatures(SparkMLEncoder encoder) {
    MinMaxScalerModel transformer = getTransformer();
    double rescaleFactor = (transformer.getMax() - transformer.getMin());
    double rescaleConstant = transformer.getMin();
    List<Feature> features = encoder.getFeatures(transformer.getInputCol());
    Vector originalMax = transformer.originalMax();
    if (originalMax.size() != features.size()) {
        throw new IllegalArgumentException();
    }
    Vector originalMin = transformer.originalMin();
    if (originalMin.size() != features.size()) {
        throw new IllegalArgumentException();
    }
    List<Feature> result = new ArrayList<>();
    for (int i = 0; i < features.size(); i++) {
        Feature feature = features.get(i);
        ContinuousFeature continuousFeature = feature.toContinuousFeature();
        double max = originalMax.apply(i);
        double min = originalMin.apply(i);
        Expression expression = PMMLUtil.createApply("/", PMMLUtil.createApply("-", continuousFeature.ref(), PMMLUtil.createConstant(min)), PMMLUtil.createConstant(max - min));
        if (!ValueUtil.isOne(rescaleFactor)) {
            expression = PMMLUtil.createApply("*", expression, PMMLUtil.createConstant(rescaleFactor));
        }
        if (!ValueUtil.isZero(rescaleConstant)) {
            expression = PMMLUtil.createApply("+", expression, PMMLUtil.createConstant(rescaleConstant));
        }
        DerivedField derivedField = encoder.createDerivedField(formatName(transformer, i), OpType.CONTINUOUS, DataType.DOUBLE, expression);
        result.add(new ContinuousFeature(encoder, derivedField));
    }
    return result;
}

Example 22 with Expression

use of org.dmg.pmml.Expression in project jpmml-sparkml by jpmml.

the class PCAModelConverter method encodeFeatures.

@Override
public List<Feature> encodeFeatures(SparkMLEncoder encoder) {
    PCAModel transformer = getTransformer();
    List<Feature> features = encoder.getFeatures(transformer.getInputCol());
    DenseMatrix pc = transformer.pc();
    if (pc.numRows() != features.size()) {
        throw new IllegalArgumentException();
    }
    List<Feature> result = new ArrayList<>();
    for (int i = 0; i < transformer.getK(); i++) {
        Apply apply = new Apply("sum");
        for (int j = 0; j < features.size(); j++) {
            Feature feature = features.get(j);
            ContinuousFeature continuousFeature = feature.toContinuousFeature();
            Expression expression = continuousFeature.ref();
            Double coefficient = pc.apply(j, i);
            if (!ValueUtil.isOne(coefficient)) {
                expression = PMMLUtil.createApply("*", expression, PMMLUtil.createConstant(coefficient));
            }
            apply.addExpressions(expression);
        }
        DerivedField derivedField = encoder.createDerivedField(formatName(transformer, i), OpType.CONTINUOUS, DataType.DOUBLE, apply);
        result.add(new ContinuousFeature(encoder, derivedField));
    }
    return result;
}