Examples with KiePMMLClassificationTable org.kie.pmml.models.regression.model.KiePMMLClassificationTable used on opensource projects

Example 1 with KiePMMLClassificationTable

use of org.kie.pmml.models.regression.model.KiePMMLClassificationTable in project drools by kiegroup.

the class KiePMMLClassificationTableFactoryTest method getClassificationTable.

@Test
public void getClassificationTable() {
    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 targetMiningField = new MiningField();
    targetMiningField.setUsageType(MiningField.UsageType.TARGET);
    targetMiningField.setName(dataField.getName());
    MiningSchema miningSchema = new MiningSchema();
    miningSchema.addMiningFields(targetMiningField);
    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());
    KiePMMLClassificationTable retrieved = KiePMMLClassificationTableFactory.getClassificationTable(compilationDTO);
    assertNotNull(retrieved);
    assertEquals(regressionModel.getRegressionTables().size(), retrieved.getCategoryTableMap().size());
    regressionModel.getRegressionTables().forEach(regressionTable -> assertTrue(retrieved.getCategoryTableMap().containsKey(regressionTable.getTargetCategory().toString())));
    assertEquals(regressionModel.getNormalizationMethod().value(), retrieved.getRegressionNormalizationMethod().getName());
    assertEquals(OP_TYPE.CATEGORICAL, retrieved.getOpType());
    boolean isBinary = regressionModel.getRegressionTables().size() == 2;
    assertEquals(isBinary, retrieved.isBinary());
    assertEquals(isBinary, retrieved.isBinary());
    assertEquals(targetMiningField.getName().getValue(), retrieved.getTargetField());
}

Example 2 with KiePMMLClassificationTable

use of org.kie.pmml.models.regression.model.KiePMMLClassificationTable in project drools by kiegroup.

the class KiePMMLRegressionModelFactoryTest method getKiePMMLRegressionModelClasses.

@Test
public void getKiePMMLRegressionModelClasses() throws IOException, IllegalAccessException, InstantiationException {
    final CompilationDTO<RegressionModel> compilationDTO = CommonCompilationDTO.fromGeneratedPackageNameAndFields(PACKAGE_NAME, pmml, regressionModel, new HasClassLoaderMock());
    KiePMMLRegressionModel retrieved = KiePMMLRegressionModelFactory.getKiePMMLRegressionModelClasses(RegressionCompilationDTO.fromCompilationDTO(compilationDTO));
    assertNotNull(retrieved);
    assertEquals(regressionModel.getModelName(), retrieved.getName());
    assertEquals(MINING_FUNCTION.byName(regressionModel.getMiningFunction().value()), retrieved.getMiningFunction());
    assertEquals(miningFields.get(0).getName().getValue(), retrieved.getTargetField());
    final AbstractKiePMMLTable regressionTable = retrieved.getRegressionTable();
    assertNotNull(regressionTable);
    assertTrue(regressionTable instanceof KiePMMLClassificationTable);
    evaluateCategoricalRegressionTable((KiePMMLClassificationTable) regressionTable);
}

Example 3 with KiePMMLClassificationTable

use of org.kie.pmml.models.regression.model.KiePMMLClassificationTable in project drools by kiegroup.

the class KiePMMLRegressionModelFactory method getKiePMMLRegressionModelSourcesMap.

// Source code generation
public static Map<String, String> getKiePMMLRegressionModelSourcesMap(final RegressionCompilationDTO compilationDTO) throws IOException {
    logger.trace("getKiePMMLRegressionModelSourcesMap {} {} {}", compilationDTO.getFields(), compilationDTO.getModel(), compilationDTO.getPackageName());
    String className = compilationDTO.getSimpleClassName();
    CompilationUnit cloneCU = JavaParserUtils.getKiePMMLModelCompilationUnit(className, compilationDTO.getPackageName(), KIE_PMML_REGRESSION_MODEL_TEMPLATE_JAVA, KIE_PMML_REGRESSION_MODEL_TEMPLATE);
    ClassOrInterfaceDeclaration modelTemplate = cloneCU.getClassByName(className).orElseThrow(() -> new KiePMMLException(MAIN_CLASS_NOT_FOUND + ": " + className));
    Map<String, KiePMMLTableSourceCategory> tablesSourceMap = getRegressionTablesMap(compilationDTO);
    String nestedTable = tablesSourceMap.size() == 1 ? tablesSourceMap.keySet().iterator().next() : tablesSourceMap.keySet().stream().filter(tableName -> tableName.startsWith(compilationDTO.getPackageName() + ".KiePMMLClassificationTable")).findFirst().orElseThrow(() -> new KiePMMLException("Failed to find expected " + "KiePMMLClassificationTable"));
    setStaticGetter(compilationDTO, modelTemplate, nestedTable);
    Map<String, String> toReturn = tablesSourceMap.entrySet().stream().collect(Collectors.toMap(Map.Entry::getKey, entry -> entry.getValue().getSource()));
    toReturn.put(getFullClassName(cloneCU), cloneCU.toString());
    return toReturn;
}

Example 4 with KiePMMLClassificationTable

use of org.kie.pmml.models.regression.model.KiePMMLClassificationTable in project drools by kiegroup.

the class KiePMMLRegressionModelFactory method getRegressionTables.

// not-public KiePMMLRegressionModel instantiation
static Map<String, AbstractKiePMMLTable> getRegressionTables(final RegressionCompilationDTO compilationDTO) {
    Map<String, AbstractKiePMMLTable> toReturn = new HashMap<>();
    if (compilationDTO.isRegression()) {
        final List<RegressionTable> regressionTables = Collections.singletonList(compilationDTO.getModel().getRegressionTables().get(0));
        final RegressionCompilationDTO regressionCompilationDTO = RegressionCompilationDTO.fromCompilationDTORegressionTablesAndNormalizationMethod(compilationDTO, regressionTables, compilationDTO.getModel().getNormalizationMethod());
        toReturn.putAll(KiePMMLRegressionTableFactory.getRegressionTables(regressionCompilationDTO));
    } else {
        final List<RegressionTable> regressionTables = compilationDTO.getModel().getRegressionTables();
        final RegressionCompilationDTO regressionCompilationDTO = RegressionCompilationDTO.fromCompilationDTORegressionTablesAndNormalizationMethod(compilationDTO, regressionTables, RegressionModel.NormalizationMethod.NONE);
        KiePMMLClassificationTable kiePMMLClassificationTable = KiePMMLClassificationTableFactory.getClassificationTable(regressionCompilationDTO);
        toReturn.put(kiePMMLClassificationTable.getName(), kiePMMLClassificationTable);
    }
    return toReturn;
}