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Example 46 with DataField

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

the class KiePMMLTreeModelFactoryTest method getKiePMMLDroolsAST.

@Test
public void getKiePMMLDroolsAST() {
    final DataDictionary dataDictionary = pmml.getDataDictionary();
    final Map<String, KiePMMLOriginalTypeGeneratedType> fieldTypeMap = getFieldTypeMap(pmml.getDataDictionary(), pmml.getTransformationDictionary(), treeModel.getLocalTransformations());
    KiePMMLDroolsAST retrieved = KiePMMLTreeModelFactory.getKiePMMLDroolsAST(getFieldsFromDataDictionary(dataDictionary), treeModel, fieldTypeMap, Collections.emptyList());
    assertNotNull(retrieved);
    List<DataField> dataFields = dataDictionary.getDataFields();
    assertEquals(dataFields.size(), fieldTypeMap.size());
    dataFields.forEach(dataField -> assertTrue(fieldTypeMap.containsKey(dataField.getName().getValue())));
}
Also used : KiePMMLDroolsAST(org.kie.pmml.models.drools.ast.KiePMMLDroolsAST) DataField(org.dmg.pmml.DataField) DataDictionary(org.dmg.pmml.DataDictionary) CommonTestingUtils.getFieldsFromDataDictionary(org.kie.pmml.compiler.api.CommonTestingUtils.getFieldsFromDataDictionary) KiePMMLOriginalTypeGeneratedType(org.kie.pmml.models.drools.tuples.KiePMMLOriginalTypeGeneratedType) Test(org.junit.Test)

Example 47 with DataField

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

the class KiePMMLRegressionTableFactoryTest method getRegressionTable.

@Test
public void getRegressionTable() {
    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());
    KiePMMLRegressionTable retrieved = KiePMMLRegressionTableFactory.getRegressionTable(regressionTable, compilationDTO);
    assertNotNull(retrieved);
    commonEvaluateRegressionTable(retrieved, regressionTable);
}
Also used : MiningField(org.dmg.pmml.MiningField) DataField(org.dmg.pmml.DataField) MiningSchema(org.dmg.pmml.MiningSchema) KiePMMLRegressionTable(org.kie.pmml.models.regression.model.KiePMMLRegressionTable) PMML(org.dmg.pmml.PMML) RegressionCompilationDTO(org.kie.pmml.models.regression.compiler.dto.RegressionCompilationDTO) DataDictionary(org.dmg.pmml.DataDictionary) HasClassLoaderMock(org.kie.pmml.compiler.commons.mocks.HasClassLoaderMock) RegressionModel(org.dmg.pmml.regression.RegressionModel) Test(org.junit.Test)

Example 48 with DataField

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

the class KiePMMLRegressionTableFactoryTest method getRegressionTableBuilder.

@Test
public void getRegressionTableBuilder() {
    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.Entry<String, String> retrieved = KiePMMLRegressionTableFactory.getRegressionTableBuilder(regressionTable, compilationDTO);
    assertNotNull(retrieved);
    Map<String, String> sources = new HashMap<>();
    sources.put(retrieved.getKey(), retrieved.getValue());
    commonValidateCompilation(sources);
}
Also used : MiningField(org.dmg.pmml.MiningField) HashMap(java.util.HashMap) DataDictionary(org.dmg.pmml.DataDictionary) HasClassLoaderMock(org.kie.pmml.compiler.commons.mocks.HasClassLoaderMock) RegressionModel(org.dmg.pmml.regression.RegressionModel) DataField(org.dmg.pmml.DataField) MiningSchema(org.dmg.pmml.MiningSchema) PMML(org.dmg.pmml.PMML) RegressionCompilationDTO(org.kie.pmml.models.regression.compiler.dto.RegressionCompilationDTO) Map(java.util.Map) HashMap(java.util.HashMap) Test(org.junit.Test)

Example 49 with DataField

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

the class KiePMMLClassificationTableFactoryTest method getClassificationTableBuilders.

@Test
public void getClassificationTableBuilders() {
    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());
    Map<String, KiePMMLTableSourceCategory> retrieved = KiePMMLClassificationTableFactory.getClassificationTableBuilders(compilationDTO);
    assertNotNull(retrieved);
    assertEquals(3, retrieved.size());
    retrieved.values().forEach(kiePMMLTableSourceCategory -> commonValidateKiePMMLRegressionTable(kiePMMLTableSourceCategory.getSource()));
    Map<String, String> sources = retrieved.entrySet().stream().collect(Collectors.toMap(Map.Entry::getKey, stringKiePMMLTableSourceCategoryEntry -> stringKiePMMLTableSourceCategoryEntry.getValue().getSource()));
    commonValidateCompilation(sources);
}
Also used : GETKIEPMML_TABLE(org.kie.pmml.models.regression.compiler.factories.KiePMMLClassificationTableFactory.GETKIEPMML_TABLE) BeforeClass(org.junit.BeforeClass) OutputField(org.dmg.pmml.OutputField) JavaParserUtils.getFromFileName(org.kie.pmml.compiler.commons.utils.JavaParserUtils.getFromFileName) KIE_PMML_CLASSIFICATION_TABLE_TEMPLATE(org.kie.pmml.models.regression.compiler.factories.KiePMMLClassificationTableFactory.KIE_PMML_CLASSIFICATION_TABLE_TEMPLATE) ResultFeature(org.dmg.pmml.ResultFeature) MiningSchema(org.dmg.pmml.MiningSchema) OP_TYPE(org.kie.pmml.api.enums.OP_TYPE) Output(org.dmg.pmml.Output) LinkedHashMap(java.util.LinkedHashMap) FieldName(org.dmg.pmml.FieldName) OpType(org.dmg.pmml.OpType) TestCase.assertNotNull(junit.framework.TestCase.assertNotNull) KiePMMLInternalException(org.kie.pmml.api.exceptions.KiePMMLInternalException) Map(java.util.Map) Expression(com.github.javaparser.ast.expr.Expression) Assert.fail(org.junit.Assert.fail) CompilationUnit(com.github.javaparser.ast.CompilationUnit) MiningField(org.dmg.pmml.MiningField) RegressionCompilationDTO(org.kie.pmml.models.regression.compiler.dto.RegressionCompilationDTO) SUPPORTED_NORMALIZATION_METHODS(org.kie.pmml.models.regression.compiler.factories.KiePMMLClassificationTableFactory.SUPPORTED_NORMALIZATION_METHODS) JavaParserUtils(org.kie.pmml.compiler.commons.utils.JavaParserUtils) PMML(org.dmg.pmml.PMML) RegressionModel(org.dmg.pmml.regression.RegressionModel) PACKAGE_NAME(org.kie.pmml.commons.Constants.PACKAGE_NAME) Assert.assertTrue(org.junit.Assert.assertTrue) KIE_PMML_CLASSIFICATION_TABLE_TEMPLATE_JAVA(org.kie.pmml.models.regression.compiler.factories.KiePMMLClassificationTableFactory.KIE_PMML_CLASSIFICATION_TABLE_TEMPLATE_JAVA) IOException(java.io.IOException) DataDictionary(org.dmg.pmml.DataDictionary) Test(org.junit.Test) CodegenTestUtils.commonValidateCompilation(org.kie.pmml.compiler.commons.testutils.CodegenTestUtils.commonValidateCompilation) KiePMMLClassificationTable(org.kie.pmml.models.regression.model.KiePMMLClassificationTable) RegressionTable(org.dmg.pmml.regression.RegressionTable) Collectors(java.util.stream.Collectors) KiePMMLModelUtils.getGeneratedClassName(org.kie.pmml.commons.utils.KiePMMLModelUtils.getGeneratedClassName) MethodReferenceExpr(com.github.javaparser.ast.expr.MethodReferenceExpr) FileUtils.getFileContent(org.kie.test.util.filesystem.FileUtils.getFileContent) DataField(org.dmg.pmml.DataField) KiePMMLTableSourceCategory(org.kie.pmml.models.regression.model.tuples.KiePMMLTableSourceCategory) MethodDeclaration(com.github.javaparser.ast.body.MethodDeclaration) CommonCompilationDTO(org.kie.pmml.compiler.api.dto.CommonCompilationDTO) HasClassLoaderMock(org.kie.pmml.compiler.commons.mocks.HasClassLoaderMock) UNSUPPORTED_NORMALIZATION_METHODS(org.kie.pmml.models.regression.compiler.factories.KiePMMLClassificationTableFactory.UNSUPPORTED_NORMALIZATION_METHODS) ClassOrInterfaceDeclaration(com.github.javaparser.ast.body.ClassOrInterfaceDeclaration) Assert.assertEquals(org.junit.Assert.assertEquals) MiningField(org.dmg.pmml.MiningField) DataDictionary(org.dmg.pmml.DataDictionary) HasClassLoaderMock(org.kie.pmml.compiler.commons.mocks.HasClassLoaderMock) RegressionTable(org.dmg.pmml.regression.RegressionTable) RegressionModel(org.dmg.pmml.regression.RegressionModel) DataField(org.dmg.pmml.DataField) MiningSchema(org.dmg.pmml.MiningSchema) Output(org.dmg.pmml.Output) KiePMMLTableSourceCategory(org.kie.pmml.models.regression.model.tuples.KiePMMLTableSourceCategory) OutputField(org.dmg.pmml.OutputField) PMML(org.dmg.pmml.PMML) RegressionCompilationDTO(org.kie.pmml.models.regression.compiler.dto.RegressionCompilationDTO) LinkedHashMap(java.util.LinkedHashMap) Map(java.util.Map) Test(org.junit.Test)

Example 50 with DataField

use of org.dmg.pmml.DataField 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());
}
Also used : MiningField(org.dmg.pmml.MiningField) DataDictionary(org.dmg.pmml.DataDictionary) HasClassLoaderMock(org.kie.pmml.compiler.commons.mocks.HasClassLoaderMock) RegressionTable(org.dmg.pmml.regression.RegressionTable) RegressionModel(org.dmg.pmml.regression.RegressionModel) DataField(org.dmg.pmml.DataField) MiningSchema(org.dmg.pmml.MiningSchema) Output(org.dmg.pmml.Output) OutputField(org.dmg.pmml.OutputField) PMML(org.dmg.pmml.PMML) RegressionCompilationDTO(org.kie.pmml.models.regression.compiler.dto.RegressionCompilationDTO) KiePMMLClassificationTable(org.kie.pmml.models.regression.model.KiePMMLClassificationTable) Test(org.junit.Test)

Aggregations

DataField (org.dmg.pmml.DataField)101 Test (org.junit.Test)51 DataDictionary (org.dmg.pmml.DataDictionary)42 MiningField (org.dmg.pmml.MiningField)42 MiningSchema (org.dmg.pmml.MiningSchema)30 PMMLModelTestUtils.getRandomDataField (org.kie.pmml.compiler.api.testutils.PMMLModelTestUtils.getRandomDataField)28 RegressionModel (org.dmg.pmml.regression.RegressionModel)27 CommonTestingUtils.getFieldsFromDataDictionary (org.kie.pmml.compiler.api.CommonTestingUtils.getFieldsFromDataDictionary)27 FieldName (org.dmg.pmml.FieldName)24 Model (org.dmg.pmml.Model)24 PMMLModelTestUtils.getDataField (org.kie.pmml.compiler.api.testutils.PMMLModelTestUtils.getDataField)22 DataType (org.dmg.pmml.DataType)19 OutputField (org.dmg.pmml.OutputField)19 PMMLModelTestUtils.getRandomMiningField (org.kie.pmml.compiler.api.testutils.PMMLModelTestUtils.getRandomMiningField)19 PMMLModelTestUtils.getMiningField (org.kie.pmml.compiler.api.testutils.PMMLModelTestUtils.getMiningField)18 ArrayList (java.util.ArrayList)17 List (java.util.List)17 PMML (org.dmg.pmml.PMML)17 Collectors (java.util.stream.Collectors)16 OpType (org.dmg.pmml.OpType)15