question: @ Override public AggregateableEvaluation aggregate ( Evaluation evaluation ) { m_Incorrect += evaluation . incorrect ( ) ; m_Correct += evaluation . correct ( ) ; m_Unclassified += evaluation . unclassified ( ) ; m_MissingClass += evaluation . m_MissingClass ; m_WithClass += evaluation . m_WithClass ; if ( evaluation . m_ConfusionMatrix != null ) { double [ ] [ ] newMatrix = evaluation . confusionMatrix ( ) ; if ( newMatrix != null ) { for ( int i = 0 ; i < m_ConfusionMatrix . length ; i ++ ) { for ( int j = 0 ; j < m_ConfusionMatrix [ i ] . length ; j ++ ) { m_ConfusionMatrix [ i ] [ j ] += newMatrix [ i ] [ j ] ; } } } } double [ ] newClassPriors = evaluation . m_ClassPriors ; if ( newClassPriors != null && m_ClassPriors != null ) { for ( int i = 0 ; i < this . m_ClassPriors . length ; i ++ ) { m_ClassPriors [ i ] = newClassPriors [ i ] ; } } m_ClassPriorsSum = evaluation . m_ClassPriorsSum ; m_TotalCost += evaluation . totalCost ( ) ; m_SumErr += evaluation . m_SumErr ; m_SumAbsErr += evaluation . m_SumAbsErr ; m_SumSqrErr += evaluation . m_SumSqrErr ; m_SumClass += evaluation . m_SumClass ; m_SumSqrClass += evaluation . m_SumSqrClass ; m_SumPredicted += evaluation . m_SumPredicted ; m_SumSqrPredicted += evaluation . m_SumSqrPredicted ; m_SumClassPredicted += evaluation . m_SumClassPredicted ; m_SumPriorAbsErr += evaluation . m_SumPriorAbsErr ; m_SumPriorSqrErr += evaluation . m_SumPriorSqrErr ; m_SumKBInfo += evaluation . m_SumKBInfo ; double [ ] newMarginCounts = evaluation . m_MarginCounts ; if ( newMarginCounts != null ) { for ( int i = 0 ; i < m_MarginCounts . length ; i ++ ) { m_MarginCounts [ i ] += newMarginCounts [ i ] ; } } m_ComplexityStatisticsAvailable = evaluation . m_ComplexityStatisticsAvailable ; m_CoverageStatisticsAvailable = evaluation . m_CoverageStatisticsAvailable ; m_SumPriorEntropy += evaluation . m_SumPriorEntropy ; m_SumSchemeEntropy += evaluation . m_SumSchemeEntropy ; m_TotalSizeOfRegions += evaluation . m_TotalSizeOfRegions ; m_TotalCoverage += evaluation . m_TotalCoverage ; ArrayList < Prediction > predsToAdd = evaluation . m_Predictions ; if ( predsToAdd != null ) { if ( m_Predictions == null ) { m_Predictions = new ArrayList < Prediction > ( ) ; } for ( int i = 0 ; i < predsToAdd . size ( ) ; i ++ ) { m_Predictions . add ( predsToAdd . get ( i ) ) ; } } return this ; }
target:  Adds the statistics encapsulated in the supplied Evaluation object into this one. Does not perform any checks for compatibility between the supplied Evaluation object and this one.