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

Example 1 with OPTYPE

use of org.dmg.pmml.OPTYPE in project drools by kiegroup.

the class KiePMMLUtil method getTargetDataField.

/**
 * Returns a model-specific <b>target</b> <code>DataField</code>
 * @param model
 * @return
 */
static Optional<DataField> getTargetDataField(final Model model) {
    DataType targetDataType = getTargetDataType(model.getMiningFunction(), model.getMathContext());
    OpType targetOpType = getTargetOpType(model.getMiningFunction());
    if (targetDataType == null || targetOpType == null) {
        return Optional.empty();
    }
    String cleanedName = model.getModelName().replaceAll("[^A-Za-z0-9]", "");
    String fieldName = String.format(TARGETFIELD_TEMPLATE, cleanedName);
    DataField toReturn = new DataField();
    toReturn.setName(FieldName.create(fieldName));
    toReturn.setOpType(targetOpType);
    toReturn.setDataType(targetDataType);
    return Optional.of(toReturn);
}

Example 2 with OPTYPE

use of org.dmg.pmml.OPTYPE in project drools by kiegroup.

the class KiePMMLUtilTest method getTargetOpType.

@Test
public void getTargetOpType() {
    MiningFunction miningFunction = MiningFunction.REGRESSION;
    OpType retrieved = KiePMMLUtil.getTargetOpType(miningFunction);
    assertEquals(OpType.CONTINUOUS, retrieved);
    miningFunction = MiningFunction.CLASSIFICATION;
    retrieved = KiePMMLUtil.getTargetOpType(miningFunction);
    assertEquals(OpType.CATEGORICAL, retrieved);
    miningFunction = MiningFunction.CLUSTERING;
    retrieved = KiePMMLUtil.getTargetOpType(miningFunction);
    assertEquals(OpType.CATEGORICAL, retrieved);
    List<MiningFunction> notMappedMiningFunctions = Arrays.asList(MiningFunction.ASSOCIATION_RULES, MiningFunction.MIXED, MiningFunction.SEQUENCES, MiningFunction.TIME_SERIES);
    notMappedMiningFunctions.forEach(minFun -> assertNull(KiePMMLUtil.getTargetOpType(minFun)));
}

Example 3 with OPTYPE

use of org.dmg.pmml.OPTYPE in project drools by kiegroup.

the class RegressionCompilationDTO method isRegression.

public boolean isRegression() {
    final DataField targetDataField = getTargetDataField();
    final OpType targetOpType = targetDataField != null ? targetDataField.getOpType() : null;
    return Objects.equals(MiningFunction.REGRESSION, getMiningFunction()) && (targetDataField == null || Objects.equals(OpType.CONTINUOUS, targetOpType));
}

Example 4 with OPTYPE

use of org.dmg.pmml.OPTYPE in project knime-core by knime.

the class PMMLStringConversionTranslator method createDerivedFields.

private DerivedField[] createDerivedFields() {
    DATATYPE.Enum dataType = PMMLDataDictionaryTranslator.getPMMLDataType(m_parseType);
    OPTYPE.Enum optype = PMMLDataDictionaryTranslator.getOptype(m_parseType);
    int num = m_includeCols.size();
    DerivedField[] derivedFields = new DerivedField[num];
    for (int i = 0; i < num; i++) {
        DerivedField df = DerivedField.Factory.newInstance();
        String name = m_includeCols.get(i);
        df.setDisplayName(name);
        /* The field name must be retrieved before creating a new derived
             * name for this derived field as the map only contains the
             * current mapping. */
        String fieldName = m_mapper.getDerivedFieldName(name);
        df.setName(m_mapper.createDerivedFieldName(name));
        df.setDataType(dataType);
        df.setOptype(optype);
        FieldRef fieldRef = df.addNewFieldRef();
        fieldRef.setField(fieldName);
        derivedFields[i] = df;
    }
    return derivedFields;
}

Example 5 with OPTYPE

use of org.dmg.pmml.OPTYPE in project knime-core by knime.

the class PMMLStringConversionTranslator method createDerivedFields.

private DerivedField[] createDerivedFields() {
    DATATYPE.Enum dataType = PMMLDataDictionaryTranslator.getPMMLDataType(m_parseType);
    OPTYPE.Enum optype = PMMLDataDictionaryTranslator.getOptype(m_parseType);
    int num = m_includeCols.size();
    DerivedField[] derivedFields = new DerivedField[num];
    for (int i = 0; i < num; i++) {
        DerivedField df = DerivedField.Factory.newInstance();
        String name = m_includeCols.get(i);
        df.setDisplayName(name);
        /* The field name must be retrieved before creating a new derived
             * name for this derived field as the map only contains the
             * current mapping. */
        String fieldName = m_mapper.getDerivedFieldName(name);
        df.setName(m_mapper.createDerivedFieldName(name));
        df.setDataType(dataType);
        df.setOptype(optype);
        FieldRef fieldRef = df.addNewFieldRef();
        fieldRef.setField(fieldName);
        derivedFields[i] = df;
    }
    return derivedFields;
}