Package org.dmg.pmml.pmml_4_2.descr

Examples of org.dmg.pmml.pmml_4_2.descr.UniformDistribution

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            return "new Double[] { " + pd.getMean() + " }";
        } else if ( d instanceof UniformDistribution ) {
            UniformDistribution ud = (UniformDistribution) d;
            return "new Double[] { " + ud.getLower() + ", " + ud.getUpper() + " }";
        } else if ( d instanceof AnyDistribution ) {
            AnyDistribution ad = (AnyDistribution) d;
            return "new Double[] { " + ad.getMean() + ", " + ad.getVariance() + " }";
        }
        throw new IllegalStateException( "Unrecognized Distribution type " + d.getClass().getName() );
    }
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            extension.setName( PMMLExtensionNames.EXTERNAL_CLASS );
            extension.setValue( characteristic.getFact() );
            miningField.getExtensions().add( extension );

            for ( final org.drools.workbench.models.guided.scorecard.shared.Attribute attribute : characteristic.getAttributes() ) {
                final Attribute _attribute = new Attribute();
                _characteristic.getAttributes().add( _attribute );

                extension = new Extension();
                extension.setName( ScorecardPMMLExtensionNames.CHARACTERTISTIC_FIELD );
                extension.setValue( characteristic.getField() );
                _attribute.getExtensions().add( extension );

                if ( model.isUseReasonCodes() ) {
                    _attribute.setReasonCode( attribute.getReasonCode() );
                }
                _attribute.setPartialScore( attribute.getPartialScore() );

                final String operator = attribute.getOperator();
                final String dataType = characteristic.getDataType();
                String predicateResolver;
                if ( "boolean".equalsIgnoreCase( dataType ) ) {
                    predicateResolver = operator.toUpperCase();
                } else if ( "String".equalsIgnoreCase( dataType ) ) {
                    if ( operator.contains( "=" ) ) {
                        predicateResolver = operator + attribute.getValue();
                    } else {
                        predicateResolver = attribute.getValue() + ",";
                    }
                } else {
                    if ( NUMERIC_OPERATORS.contains( operator ) ) {
                        predicateResolver = operator + " " + attribute.getValue();
                    } else {
                        predicateResolver = attribute.getValue().replace( ",", "-" );
                    }
                }
                extension = new Extension();
                extension.setName( "predicateResolver" );
                extension.setValue( predicateResolver );
                _attribute.getExtensions().add( extension );
            }
        }

        pmmlScorecard.getExtensionsAndCharacteristicsAndMiningSchemas().add( miningSchema );
        pmmlScorecard.getExtensionsAndCharacteristicsAndMiningSchemas().add( output );
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            extension.setName( PMMLExtensionNames.EXTERNAL_CLASS );
            extension.setValue( characteristic.getFact() );
            miningField.getExtensions().add( extension );

            for ( final org.drools.workbench.models.guided.scorecard.shared.Attribute attribute : characteristic.getAttributes() ) {
                final Attribute _attribute = new Attribute();
                _characteristic.getAttributes().add( _attribute );

                extension = new Extension();
                extension.setName( ScorecardPMMLExtensionNames.CHARACTERTISTIC_FIELD );
                extension.setValue( characteristic.getField() );
                _attribute.getExtensions().add( extension );

                if ( model.isUseReasonCodes() ) {
                    _attribute.setReasonCode( attribute.getReasonCode() );
                }
                _attribute.setPartialScore( attribute.getPartialScore() );

                final String operator = attribute.getOperator();
                final String dataType = characteristic.getDataType();
                String predicateResolver;
                if ( "boolean".equalsIgnoreCase( dataType ) ) {
                    predicateResolver = operator.toUpperCase();
                } else if ( "String".equalsIgnoreCase( dataType ) ) {
                    if ( operator.contains( "=" ) ) {
                        predicateResolver = operator + attribute.getValue();
                    } else {
                        predicateResolver = attribute.getValue() + ",";
                    }
                } else {
                    if ( NUMERIC_OPERATORS.contains( operator ) ) {
                        predicateResolver = operator + " " + attribute.getValue();
                    } else {
                        predicateResolver = attribute.getValue().replace( ",", "-" );
                    }
                }
                extension = new Extension();
                extension.setName( "predicateResolver" );
                extension.setValue( predicateResolver );
                _attribute.getExtensions().add( extension );
            }
        }

        pmmlScorecard.getExtensionsAndCharacteristicsAndMiningSchemas().add( miningSchema );
        pmmlScorecard.getExtensionsAndCharacteristicsAndMiningSchemas().add( output );
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            pmmlScorecard.setBaselineScore( model.getBaselineScore() );
            pmmlScorecard.setReasonCodeAlgorithm( model.getReasonCodesAlgorithm() );
        }

        for ( final org.drools.workbench.models.guided.scorecard.shared.Characteristic characteristic : model.getCharacteristics() ) {
            final Characteristic _characteristic = new Characteristic();
            characteristics.getCharacteristics().add( _characteristic );

            extension = new Extension();
            extension.setName( PMMLExtensionNames.EXTERNAL_CLASS );
            extension.setValue( characteristic.getFact() );
            _characteristic.getExtensions().add( extension );

            extension = new Extension();
            extension.setName( ScorecardPMMLExtensionNames.CHARACTERTISTIC_DATATYPE );
            if ( "string".equalsIgnoreCase( characteristic.getDataType() ) ) {
                extension.setValue( XLSKeywords.DATATYPE_TEXT );
            } else if ( "int".equalsIgnoreCase( characteristic.getDataType() ) || "double".equalsIgnoreCase( characteristic.getDataType() ) ) {
                extension.setValue( XLSKeywords.DATATYPE_NUMBER );
            } else if ( "boolean".equalsIgnoreCase( characteristic.getDataType() ) ) {
                extension.setValue( XLSKeywords.DATATYPE_BOOLEAN );
            } else {
                System.out.println( ">>>> Found unknown data type :: " + characteristic.getDataType() );
            }
            _characteristic.getExtensions().add( extension );

            _characteristic.setBaselineScore( characteristic.getBaselineScore() );
            if ( model.isUseReasonCodes() ) {
                _characteristic.setReasonCode( characteristic.getReasonCode() );
            }
            _characteristic.setName( characteristic.getName() );

            final MiningField miningField = new MiningField();
            miningField.setName( characteristic.getField() );
            miningField.setUsageType( FIELDUSAGETYPE.ACTIVE );
            miningField.setInvalidValueTreatment( INVALIDVALUETREATMENTMETHOD.RETURN_INVALID );
            miningSchema.getMiningFields().add( miningField );

            extension = new Extension();
            extension.setName( PMMLExtensionNames.EXTERNAL_CLASS );
            extension.setValue( characteristic.getFact() );
            miningField.getExtensions().add( extension );

            for ( final org.drools.workbench.models.guided.scorecard.shared.Attribute attribute : characteristic.getAttributes() ) {
                final Attribute _attribute = new Attribute();
                _characteristic.getAttributes().add( _attribute );

                extension = new Extension();
                extension.setName( ScorecardPMMLExtensionNames.CHARACTERTISTIC_FIELD );
                extension.setValue( characteristic.getField() );
                _attribute.getExtensions().add( extension );
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            pmmlScorecard.setBaselineScore( model.getBaselineScore() );
            pmmlScorecard.setReasonCodeAlgorithm( model.getReasonCodesAlgorithm() );
        }

        for ( final org.drools.workbench.models.guided.scorecard.shared.Characteristic characteristic : model.getCharacteristics() ) {
            final Characteristic _characteristic = new Characteristic();
            characteristics.getCharacteristics().add( _characteristic );

            extension = new Extension();
            extension.setName( PMMLExtensionNames.EXTERNAL_CLASS );
            extension.setValue( characteristic.getFact() );
            _characteristic.getExtensions().add( extension );

            extension = new Extension();
            extension.setName( ScorecardPMMLExtensionNames.CHARACTERTISTIC_DATATYPE );
            if ( "string".equalsIgnoreCase( characteristic.getDataType() ) ) {
                extension.setValue( XLSKeywords.DATATYPE_TEXT );
            } else if ( "int".equalsIgnoreCase( characteristic.getDataType() ) || "double".equalsIgnoreCase( characteristic.getDataType() ) ) {
                extension.setValue( XLSKeywords.DATATYPE_NUMBER );
            } else if ( "boolean".equalsIgnoreCase( characteristic.getDataType() ) ) {
                extension.setValue( XLSKeywords.DATATYPE_BOOLEAN );
            } else {
                System.out.println( ">>>> Found unknown data type :: " + characteristic.getDataType() );
            }
            _characteristic.getExtensions().add( extension );

            _characteristic.setBaselineScore( characteristic.getBaselineScore() );
            if ( model.isUseReasonCodes() ) {
                _characteristic.setReasonCode( characteristic.getReasonCode() );
            }
            _characteristic.setName( characteristic.getName() );

            final MiningField miningField = new MiningField();
            miningField.setName( characteristic.getField() );
            miningField.setUsageType( FIELDUSAGETYPE.ACTIVE );
            miningField.setInvalidValueTreatment( INVALIDVALUETREATMENTMETHOD.RETURN_INVALID );
            miningSchema.getMiningFields().add( miningField );

            extension = new Extension();
            extension.setName( PMMLExtensionNames.EXTERNAL_CLASS );
            extension.setValue( characteristic.getFact() );
            miningField.getExtensions().add( extension );

            for ( final org.drools.workbench.models.guided.scorecard.shared.Attribute attribute : characteristic.getAttributes() ) {
                final Attribute _attribute = new Attribute();
                _characteristic.getAttributes().add( _attribute );

                extension = new Extension();
                extension.setName( ScorecardPMMLExtensionNames.CHARACTERTISTIC_FIELD );
                extension.setValue( characteristic.getField() );
                _attribute.getExtensions().add( extension );
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    }

    private void checkForInvalidDataTypes() {
        for (Object obj :scorecard.getExtensionsAndCharacteristicsAndMiningSchemas()){
            if (obj instanceof Characteristics){
                Characteristics characteristics = (Characteristics)obj;
                for (Characteristic characteristic : characteristics.getCharacteristics()){
                    String dataType = ScorecardPMMLUtils.getExtensionValue(characteristic.getExtensions(), ScorecardPMMLExtensionNames.CHARACTERTISTIC_DATATYPE);
                    String newCellRef = createDataTypeCellRef(ScorecardPMMLUtils.getExtensionValue(characteristic.getExtensions(), "cellRef"),1);
                    if ( dataType == null || StringUtils.isEmpty(dataType)) {
                        parseErrors.add(new ScorecardError(newCellRef, "Missing Data Type!"));
                    }  else  if ( !XLSKeywords.DATATYPE_TEXT.equalsIgnoreCase(dataType) && !XLSKeywords.DATATYPE_NUMBER.equalsIgnoreCase(dataType)  && !XLSKeywords.DATATYPE_BOOLEAN.equalsIgnoreCase(dataType)){
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    }

    private void checkForMissingAttributes() {
        for (Object obj :scorecard.getExtensionsAndCharacteristicsAndMiningSchemas()){
            if (obj instanceof Characteristics){
                Characteristics characteristics = (Characteristics)obj;
                for (Characteristic characteristic : characteristics.getCharacteristics()){
                    String newCellRef = ScorecardPMMLUtils.getExtensionValue(characteristic.getExtensions(), "cellRef");
                    if ( characteristic.getAttributes().size() == 0 ) {
                        parseErrors.add(new ScorecardError(newCellRef, "Missing Attribute Bins for Characteristic '"+characteristic.getName()+"'."));
                    }
                }
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    }

    private void validateWeights() {
        for (Object obj :scorecard.getExtensionsAndCharacteristicsAndMiningSchemas()){
            if (obj instanceof Characteristics){
                Characteristics characteristics = (Characteristics)obj;
                for (Characteristic characteristic : characteristics.getCharacteristics()){
                    for (Attribute attribute : characteristic.getAttributes()){
                        String newCellRef = createDataTypeCellRef(ScorecardPMMLUtils.getExtensionValue(attribute.getExtensions(), "cellRef"),2);
                        String weight = ScorecardPMMLUtils.getExtensionValue(attribute.getExtensions(), ScorecardPMMLExtensionNames.CHARACTERTISTIC_WEIGHT);
                        if ( StringUtils.isEmpty(weight) || !isDouble(weight)){
                            parseErrors.add(new ScorecardError(newCellRef, "Attribute is missing weight or specified weight is not a double."));
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    }

    private void validateReasonCodes() {
        for (Object obj :scorecard.getExtensionsAndCharacteristicsAndMiningSchemas()){
            if (obj instanceof Characteristics){
                Characteristics characteristics = (Characteristics)obj;
                for (Characteristic characteristic : characteristics.getCharacteristics()){
                    String charReasonCode = characteristic.getReasonCode();
                    if (charReasonCode == null || StringUtils.isEmpty(charReasonCode)){
                        for (Attribute attribute : characteristic.getAttributes()){
                            String newCellRef = createDataTypeCellRef(ScorecardPMMLUtils.getExtensionValue(attribute.getExtensions(), "cellRef"),3);
                            String attrReasonCode = attribute.getReasonCode();
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    private void validateBaselineScores() {
        for (Object obj :scorecard.getExtensionsAndCharacteristicsAndMiningSchemas()){
            Double scorecardBaseline = scorecard.getBaselineScore();
            if (obj instanceof Characteristics){
                Characteristics characteristics = (Characteristics)obj;
                for (Characteristic characteristic : characteristics.getCharacteristics()){
                    Double charBaseline = characteristic.getBaselineScore();
                    if  ( (charBaseline == null || charBaseline.doubleValue() == 0)
                            && ((scorecardBaseline == null || scorecardBaseline.doubleValue() == 0)) ){
                        String newCellRef = createDataTypeCellRef(ScorecardPMMLUtils.getExtensionValue(characteristic.getExtensions(), "cellRef"),2);
                        parseErrors.add(new ScorecardError(newCellRef, "Characteristic is missing Baseline Score"));
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Related Classes of org.dmg.pmml.pmml_4_2.descr.UniformDistribution

  • org.drools.pmml.pmml_4_2.PMML4Compiler
  • org.drools.pmml.pmml_4_2.PMML4Helper
  • org.drools.pmml.pmml_4_2.PMMLGenerationTest
  • org.drools.pmml.pmml_4_2.predictive.models.DecisionTreeTest
  • org.drools.scorecards.DrlFromPMMLTest
  • org.drools.scorecards.ExternalObjectModelTest
  • org.drools.scorecards.parser.xls.ExcelScorecardValidator
  • org.drools.scorecards.ScorecardReasonCodeTest
  • org.drools.scorecards.ScoringStrategiesTest
  • org.drools.workbench.models.guided.scorecard.backend.GuidedScoreCardDRLPersistence
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