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

Example 51 with MiningField

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

the class KiePMMLClassificationTableFactoryTest method getClassificationTableBuilder.

@Test
public void getClassificationTableBuilder() {
    RegressionTable regressionTableProf = getRegressionTable(3.5, "professional");
    RegressionTable regressionTableCler = getRegressionTable(27.4, "clerical");
    OutputField outputFieldCat = getOutputField("CAT-1", ResultFeature.PROBABILITY, "CatPred-1");
    OutputField outputFieldNum = getOutputField("NUM-1", ResultFeature.PROBABILITY, "NumPred-0");
    OutputField outputFieldPrev = getOutputField("PREV", ResultFeature.PREDICTED_VALUE, null);
    String targetField = "targetField";
    DataField dataField = new DataField();
    dataField.setName(FieldName.create(targetField));
    dataField.setOpType(OpType.CATEGORICAL);
    DataDictionary dataDictionary = new DataDictionary();
    dataDictionary.addDataFields(dataField);
    RegressionModel regressionModel = new RegressionModel();
    regressionModel.setNormalizationMethod(RegressionModel.NormalizationMethod.CAUCHIT);
    regressionModel.addRegressionTables(regressionTableProf, regressionTableCler);
    regressionModel.setModelName(getGeneratedClassName("RegressionModel"));
    Output output = new Output();
    output.addOutputFields(outputFieldCat, outputFieldNum, outputFieldPrev);
    regressionModel.setOutput(output);
    MiningField miningField = new MiningField();
    miningField.setUsageType(MiningField.UsageType.TARGET);
    miningField.setName(dataField.getName());
    MiningSchema miningSchema = new MiningSchema();
    miningSchema.addMiningFields(miningField);
    regressionModel.setMiningSchema(miningSchema);
    PMML pmml = new PMML();
    pmml.setDataDictionary(dataDictionary);
    pmml.addModels(regressionModel);
    final CommonCompilationDTO<RegressionModel> source = CommonCompilationDTO.fromGeneratedPackageNameAndFields(PACKAGE_NAME, pmml, regressionModel, new HasClassLoaderMock());
    final RegressionCompilationDTO compilationDTO = RegressionCompilationDTO.fromCompilationDTORegressionTablesAndNormalizationMethod(source, regressionModel.getRegressionTables(), regressionModel.getNormalizationMethod());
    final LinkedHashMap<String, KiePMMLTableSourceCategory> regressionTablesMap = new LinkedHashMap<>();
    regressionModel.getRegressionTables().forEach(regressionTable -> {
        String key = compilationDTO.getPackageName() + "." + regressionTable.getTargetCategory().toString().toUpperCase();
        KiePMMLTableSourceCategory value = new KiePMMLTableSourceCategory("", regressionTable.getTargetCategory().toString());
        regressionTablesMap.put(key, value);
    });
    Map.Entry<String, String> retrieved = KiePMMLClassificationTableFactory.getClassificationTableBuilder(compilationDTO, regressionTablesMap);
    assertNotNull(retrieved);
}

Example 52 with MiningField

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

the class KiePMMLRegressionTableFactoryTest method getRegressionTableBuilders.

@Test
public void getRegressionTableBuilders() {
    regressionTable = getRegressionTable(3.5, "professional");
    RegressionModel regressionModel = new RegressionModel();
    regressionModel.setNormalizationMethod(RegressionModel.NormalizationMethod.CAUCHIT);
    regressionModel.addRegressionTables(regressionTable);
    regressionModel.setModelName(getGeneratedClassName("RegressionModel"));
    String targetField = "targetField";
    DataField dataField = new DataField();
    dataField.setName(FieldName.create(targetField));
    dataField.setOpType(OpType.CATEGORICAL);
    DataDictionary dataDictionary = new DataDictionary();
    dataDictionary.addDataFields(dataField);
    MiningField miningField = new MiningField();
    miningField.setUsageType(MiningField.UsageType.TARGET);
    miningField.setName(dataField.getName());
    MiningSchema miningSchema = new MiningSchema();
    miningSchema.addMiningFields(miningField);
    regressionModel.setMiningSchema(miningSchema);
    PMML pmml = new PMML();
    pmml.setDataDictionary(dataDictionary);
    pmml.addModels(regressionModel);
    final CommonCompilationDTO<RegressionModel> source = CommonCompilationDTO.fromGeneratedPackageNameAndFields(PACKAGE_NAME, pmml, regressionModel, new HasClassLoaderMock());
    final RegressionCompilationDTO compilationDTO = RegressionCompilationDTO.fromCompilationDTORegressionTablesAndNormalizationMethod(source, new ArrayList<>(), regressionModel.getNormalizationMethod());
    Map<String, KiePMMLTableSourceCategory> retrieved = KiePMMLRegressionTableFactory.getRegressionTableBuilders(compilationDTO);
    assertNotNull(retrieved);
    retrieved.values().forEach(kiePMMLTableSourceCategory -> commonValidateKiePMMLRegressionTable(kiePMMLTableSourceCategory.getSource()));
}

Example 53 with MiningField

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

the class KiePMMLRegressionTableFactoryTest method getRegressionTables.

@Test
public void getRegressionTables() {
    regressionTable = getRegressionTable(3.5, "professional");
    RegressionTable regressionTable2 = getRegressionTable(3.9, "hobby");
    RegressionModel regressionModel = new RegressionModel();
    regressionModel.setNormalizationMethod(RegressionModel.NormalizationMethod.CAUCHIT);
    regressionModel.addRegressionTables(regressionTable, regressionTable2);
    regressionModel.setModelName(getGeneratedClassName("RegressionModel"));
    String targetField = "targetField";
    DataField dataField = new DataField();
    dataField.setName(FieldName.create(targetField));
    dataField.setOpType(OpType.CATEGORICAL);
    DataDictionary dataDictionary = new DataDictionary();
    dataDictionary.addDataFields(dataField);
    MiningField miningField = new MiningField();
    miningField.setUsageType(MiningField.UsageType.TARGET);
    miningField.setName(dataField.getName());
    MiningSchema miningSchema = new MiningSchema();
    miningSchema.addMiningFields(miningField);
    regressionModel.setMiningSchema(miningSchema);
    PMML pmml = new PMML();
    pmml.setDataDictionary(dataDictionary);
    pmml.addModels(regressionModel);
    final CommonCompilationDTO<RegressionModel> source = CommonCompilationDTO.fromGeneratedPackageNameAndFields(PACKAGE_NAME, pmml, regressionModel, new HasClassLoaderMock());
    final RegressionCompilationDTO compilationDTO = RegressionCompilationDTO.fromCompilationDTORegressionTablesAndNormalizationMethod(source, regressionModel.getRegressionTables(), regressionModel.getNormalizationMethod());
    Map<String, KiePMMLRegressionTable> retrieved = KiePMMLRegressionTableFactory.getRegressionTables(compilationDTO);
    assertNotNull(retrieved);
    assertEquals(regressionModel.getRegressionTables().size(), retrieved.size());
    regressionModel.getRegressionTables().forEach(regrTabl -> {
        assertTrue(retrieved.containsKey(regrTabl.getTargetCategory().toString()));
        commonEvaluateRegressionTable(retrieved.get(regrTabl.getTargetCategory().toString()), regrTabl);
    });
}

Example 54 with MiningField

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

the class KiePMMLRegressionTableFactoryTest method setStaticGetter.

@Test
public void setStaticGetter() throws IOException {
    regressionTable = getRegressionTable(3.5, "professional");
    RegressionModel regressionModel = new RegressionModel();
    regressionModel.setNormalizationMethod(RegressionModel.NormalizationMethod.CAUCHIT);
    regressionModel.addRegressionTables(regressionTable);
    regressionModel.setModelName(getGeneratedClassName("RegressionModel"));
    String targetField = "targetField";
    DataField dataField = new DataField();
    dataField.setName(FieldName.create(targetField));
    dataField.setOpType(OpType.CATEGORICAL);
    DataDictionary dataDictionary = new DataDictionary();
    dataDictionary.addDataFields(dataField);
    MiningField miningField = new MiningField();
    miningField.setUsageType(MiningField.UsageType.TARGET);
    miningField.setName(dataField.getName());
    MiningSchema miningSchema = new MiningSchema();
    miningSchema.addMiningFields(miningField);
    regressionModel.setMiningSchema(miningSchema);
    PMML pmml = new PMML();
    pmml.setDataDictionary(dataDictionary);
    pmml.addModels(regressionModel);
    String variableName = "variableName";
    final CommonCompilationDTO<RegressionModel> source = CommonCompilationDTO.fromGeneratedPackageNameAndFields(PACKAGE_NAME, pmml, regressionModel, new HasClassLoaderMock());
    final RegressionCompilationDTO compilationDTO = RegressionCompilationDTO.fromCompilationDTORegressionTablesAndNormalizationMethod(source, new ArrayList<>(), regressionModel.getNormalizationMethod());
    final MethodDeclaration staticGetterMethod = STATIC_GETTER_METHOD.clone();
    KiePMMLRegressionTableFactory.setStaticGetter(regressionTable, compilationDTO, staticGetterMethod, variableName);
    String text = getFileContent(TEST_06_SOURCE);
    MethodDeclaration expected = JavaParserUtils.parseMethod(text);
    assertEquals(expected.toString(), staticGetterMethod.toString());
    assertTrue(JavaParserUtils.equalsNode(expected, staticGetterMethod));
    List<Class<?>> imports = Arrays.asList(AtomicReference.class, Collections.class, Arrays.class, List.class, Map.class, KiePMMLRegressionTable.class, SerializableFunction.class);
    commonValidateCompilationWithImports(staticGetterMethod, imports);
}

Example 55 with MiningField

use of org.dmg.pmml.MiningField in project shifu by ShifuML.

the class PMMLLRModelBuilder method adaptMLModelToPMML.

public RegressionModel adaptMLModelToPMML(ml.shifu.shifu.core.LR lr, RegressionModel pmmlModel) {
    pmmlModel.setNormalizationMethod(NormalizationMethod.LOGIT);
    pmmlModel.setMiningFunction(MiningFunction.REGRESSION);
    RegressionTable table = new RegressionTable();
    table.setIntercept(lr.getBias());
    LocalTransformations lt = pmmlModel.getLocalTransformations();
    List<DerivedField> df = lt.getDerivedFields();
    HashMap<FieldName, FieldName> miningTransformMap = new HashMap<FieldName, FieldName>();
    for (DerivedField dField : df) {
        // Apply z-scale normalization on numerical variables
        if (dField.getExpression() instanceof NormContinuous) {
            miningTransformMap.put(((NormContinuous) dField.getExpression()).getField(), dField.getName());
        } else // Apply bin map on categorical variables
        if (dField.getExpression() instanceof MapValues) {
            miningTransformMap.put(((MapValues) dField.getExpression()).getFieldColumnPairs().get(0).getField(), dField.getName());
        } else if (dField.getExpression() instanceof Discretize) {
            miningTransformMap.put(((Discretize) dField.getExpression()).getField(), dField.getName());
        }
    }
    List<MiningField> miningList = pmmlModel.getMiningSchema().getMiningFields();
    int index = 0;
    for (int i = 0; i < miningList.size(); i++) {
        MiningField mField = miningList.get(i);
        if (mField.getUsageType() != UsageType.ACTIVE)
            continue;
        FieldName mFieldName = mField.getName();
        FieldName fName = mFieldName;
        while (miningTransformMap.containsKey(fName)) {
            fName = miningTransformMap.get(fName);
        }
        NumericPredictor np = new NumericPredictor();
        np.setName(fName);
        np.setCoefficient(lr.getWeights()[index++]);
        table.addNumericPredictors(np);
    }
    pmmlModel.addRegressionTables(table);
    return pmmlModel;
}