Package org.dmg.pmml.pmml_4_1.descr

Examples of org.dmg.pmml.pmml_4_1.descr.Scorecard


            extension.setValue( characteristic.getFact() );
            miningField.getExtensions().add( extension );

            final String[] numericOperators = new String[]{ "=", ">", "<", ">=", "<=" };
            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( PMMLExtensionNames.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 ( ArrayUtils.contains( numericOperators, 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 );
View Full Code Here


            extension.setValue( characteristic.getFact() );
            miningField.getExtensions().add( extension );

            final String[] numericOperators = new String[]{ "=", ">", "<", ">=", "<=" };
            for ( final org.drools.guvnor.models.guided.scorecard.shared.Attribute attribute : characteristic.getAttributes() ) {
                final Attribute _attribute = new Attribute();
                _characteristic.getAttributes().add( _attribute );

                extension = new Extension();
                extension.setName( PMMLExtensionNames.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 ( ArrayUtils.contains( numericOperators, 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 );
View Full Code Here

            extension.setValue( characteristic.getFact() );
            miningField.getExtensions().add( extension );

            final String[] numericOperators = new String[]{ "=", ">", "<", ">=", "<=" };
            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( PMMLExtensionNames.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 ( ArrayUtils.contains( numericOperators, 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 );
View Full Code Here

            extension.setValue( characteristic.getFact() );
            miningField.getExtensions().add( extension );

            final String[] numericOperators = new String[]{ "=", ">", "<", ">=", "<=" };
            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 ( ArrayUtils.contains( numericOperators, 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 );
View Full Code Here

            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 );
View Full Code Here

            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.CHARACTERTISTIC_EXTERNAL_CLASS );
            extension.setValue( characteristic.getFact() );
            _characteristic.getExtensions().add( extension );

            extension = new Extension();
            extension.setName( PMMLExtensionNames.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 );

            if ( model.isUseReasonCodes() ) {
                _characteristic.setBaselineScore( characteristic.getBaselineScore() );
                _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.CHARACTERTISTIC_EXTERNAL_CLASS );
            extension.setValue( characteristic.getFact() );
            miningField.getExtensions().add( extension );

            final String[] numericOperators = new String[]{ "=", ">", "<", ">=", "<=" };
            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( PMMLExtensionNames.CHARACTERTISTIC_FIELD );
                extension.setValue( characteristic.getField() );
                _attribute.getExtensions().add( extension );
View Full Code Here

            pmmlScorecard.setBaselineScore( model.getBaselineScore() );
            pmmlScorecard.setReasonCodeAlgorithm( model.getReasonCodesAlgorithm() );
        }

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

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

            extension = new Extension();
            extension.setName( PMMLExtensionNames.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 );

            if ( model.isUseReasonCodes() ) {
                _characteristic.setBaselineScore( characteristic.getBaselineScore() );
                _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.CHARACTERTISTIC_EXTERNAL_CLASS );
            extension.setValue( characteristic.getFact() );
            miningField.getExtensions().add( extension );

            final String[] numericOperators = new String[]{ "=", ">", "<", ">=", "<=" };
            for ( final org.drools.guvnor.models.guided.scorecard.shared.Attribute attribute : characteristic.getAttributes() ) {
                final Attribute _attribute = new Attribute();
                _characteristic.getAttributes().add( _attribute );

                extension = new Extension();
                extension.setName( PMMLExtensionNames.CHARACTERTISTIC_FIELD );
                extension.setValue( characteristic.getField() );
                _attribute.getExtensions().add( extension );
View Full Code Here

            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.CHARACTERTISTIC_EXTERNAL_CLASS );
            extension.setValue( characteristic.getFact() );
            _characteristic.getExtensions().add( extension );

            extension = new Extension();
            extension.setName( PMMLExtensionNames.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 );

            if ( model.isUseReasonCodes() ) {
                _characteristic.setBaselineScore( characteristic.getBaselineScore() );
                _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.CHARACTERTISTIC_EXTERNAL_CLASS );
            extension.setValue( characteristic.getFact() );
            miningField.getExtensions().add( extension );

            final String[] numericOperators = new String[]{ "=", ">", "<", ">=", "<=" };
            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( PMMLExtensionNames.CHARACTERTISTIC_FIELD );
                extension.setValue( characteristic.getField() );
                _attribute.getExtensions().add( extension );
View Full Code Here

            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 );

            final String[] numericOperators = new String[]{ "=", ">", "<", ">=", "<=" };
            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 );
View Full Code Here

            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 );
View Full Code Here

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