/** * 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. * * @param evaluation the evaluation object to aggregate */ public void 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) { 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_SumPriorEntropy += evaluation.m_SumPriorEntropy; m_SumSchemeEntropy += evaluation.m_SumSchemeEntropy; m_TotalSizeOfRegions += evaluation.m_TotalSizeOfRegions; m_TotalCoverage += evaluation.m_TotalCoverage; FastVector predsToAdd = evaluation.m_Predictions; if (predsToAdd != null) { if (m_Predictions == null) { m_Predictions = new FastVector(); } for (int i = 0; i < predsToAdd.size(); i++) { m_Predictions.addElement(predsToAdd.elementAt(i)); } } }