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

Example 61 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.requireOpType();
    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 62 with Feature

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

the class SVMConverter method scaleFeatures.

private void scaleFeatures(RExpEncoder encoder) {
    RGenericVector svm = getObject();
    RDoubleVector sv = svm.getDoubleElement("SV");
    RBooleanVector scaled = svm.getBooleanElement("scaled");
    RGenericVector xScale = svm.getGenericElement("x.scale");
    RStringVector rowNames = sv.dimnames(0);
    RStringVector columnNames = sv.dimnames(1);
    List<Feature> features = encoder.getFeatures();
    if ((scaled.size() != columnNames.size()) || (scaled.size() != features.size())) {
        throw new IllegalArgumentException();
    }
    RDoubleVector xScaledCenter = xScale.getDoubleElement("scaled:center");
    RDoubleVector xScaledScale = xScale.getDoubleElement("scaled:scale");
    for (int i = 0; i < columnNames.size(); i++) {
        String columnName = columnNames.getValue(i);
        if (!scaled.getValue(i)) {
            continue;
        }
        Feature feature = features.get(i);
        Double center = xScaledCenter.getElement(columnName);
        Double scale = xScaledScale.getElement(columnName);
        if (ValueUtil.isZero(center) && ValueUtil.isOne(scale)) {
            continue;
        }
        ContinuousFeature continuousFeature = feature.toContinuousFeature();
        Expression expression = continuousFeature.ref();
        if (!ValueUtil.isZero(center)) {
            expression = PMMLUtil.createApply(PMMLFunctions.SUBTRACT, expression, PMMLUtil.createConstant(center));
        }
        if (!ValueUtil.isOne(scale)) {
            expression = PMMLUtil.createApply(PMMLFunctions.DIVIDE, expression, PMMLUtil.createConstant(scale));
        }
        DerivedField derivedField = encoder.createDerivedField(FieldNameUtil.create("scale", continuousFeature), OpType.CONTINUOUS, DataType.DOUBLE, expression);
        features.set(i, new ContinuousFeature(encoder, derivedField));
    }
}

Example 63 with Feature

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

the class MVRConverter method scaleFeatures.

private void scaleFeatures(RExpEncoder encoder) {
    RGenericVector mvr = getObject();
    RDoubleVector scale = mvr.getDoubleElement("scale", false);
    if (scale == null) {
        return;
    }
    List<Feature> features = encoder.getFeatures();
    if (scale.size() != features.size()) {
        throw new IllegalArgumentException();
    }
    for (int i = 0; i < features.size(); i++) {
        Feature feature = features.get(i);
        Double factor = scale.getValue(i);
        if (ValueUtil.isOne(factor)) {
            continue;
        }
        ContinuousFeature continuousFeature = feature.toContinuousFeature();
        Apply apply = PMMLUtil.createApply(PMMLFunctions.DIVIDE, continuousFeature.ref(), PMMLUtil.createConstant(factor));
        DerivedField derivedField = encoder.createDerivedField(FieldNameUtil.create("scale", continuousFeature), OpType.CONTINUOUS, DataType.DOUBLE, apply);
        features.set(i, new ContinuousFeature(encoder, derivedField));
    }
}

Example 64 with Feature

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

the class RecipeEncoder method createSchema.

@Override
public Schema createSchema() {
    RGenericVector recipe = getObject();
    Label label = getLabel();
    List<? extends Feature> features = getFeatures();
    RGenericVector steps = recipe.getGenericElement("steps");
    List<String> outcomeNames = this.termRoles.entrySet().stream().filter(entry -> (entry.getValue() == Role.OUTCOME)).map(entry -> entry.getKey()).collect(Collectors.toList());
    if (outcomeNames.size() == 1) {
        String outcomeName = outcomeNames.get(0);
        renameDataField(label.getName(), outcomeName);
        label = label.toRenamedLabel(outcomeName);
    } else if (outcomeNames.size() >= 2) {
        throw new IllegalArgumentException();
    }
    if (steps != null) {
        throw new IllegalArgumentException();
    }
    return new Schema(this, label, features);
}

Example 65 with Feature

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

the class ScorecardConverter method encodeModel.

@Override
public Scorecard encodeModel(Schema schema) {
    RGenericVector glm = getObject();
    RDoubleVector coefficients = glm.getDoubleElement("coefficients");
    RGenericVector family = glm.getGenericElement("family");
    RGenericVector scConf = DecorationUtil.getGenericElement(glm, "sc.conf");
    Double intercept = coefficients.getElement(LMConverter.INTERCEPT, false);
    List<? extends Feature> features = schema.getFeatures();
    SchemaUtil.checkSize(coefficients.size() - (intercept != null ? 1 : 0), features);
    RNumberVector<?> odds = scConf.getNumericElement("odds");
    RNumberVector<?> basePoints = scConf.getNumericElement("base_points");
    RNumberVector<?> pdo = scConf.getNumericElement("pdo");
    double factor = (pdo.asScalar()).doubleValue() / Math.log(2);
    Map<String, Characteristic> fieldCharacteristics = new LinkedHashMap<>();
    for (Feature feature : features) {
        String name = feature.getName();
        if (!(feature instanceof BinaryFeature)) {
            throw new IllegalArgumentException();
        }
        Double coefficient = getFeatureCoefficient(feature, coefficients);
        Characteristic characteristic = fieldCharacteristics.get(name);
        if (characteristic == null) {
            characteristic = new Characteristic().setName("score(" + FeatureUtil.getName(feature) + ")");
            fieldCharacteristics.put(name, characteristic);
        }
        BinaryFeature binaryFeature = (BinaryFeature) feature;
        SimplePredicate simplePredicate = new SimplePredicate(binaryFeature.getName(), SimplePredicate.Operator.EQUAL, binaryFeature.getValue());
        Attribute attribute = new Attribute(simplePredicate).setPartialScore(formatScore(-1d * coefficient * factor));
        characteristic.addAttributes(attribute);
    }
    Characteristics characteristics = new Characteristics();
    Collection<Map.Entry<String, Characteristic>> entries = fieldCharacteristics.entrySet();
    for (Map.Entry<String, Characteristic> entry : entries) {
        Characteristic characteristic = entry.getValue();
        Attribute attribute = new Attribute(True.INSTANCE).setPartialScore(0d);
        characteristic.addAttributes(attribute);
        characteristics.addCharacteristics(characteristic);
    }
    Scorecard scorecard = new Scorecard(MiningFunction.REGRESSION, ModelUtil.createMiningSchema(schema.getLabel()), characteristics).setInitialScore(formatScore((basePoints.asScalar()).doubleValue() - Math.log((odds.asScalar()).doubleValue()) * factor - (intercept != null ? intercept * factor : 0))).setUseReasonCodes(false);
    return scorecard;
}