/**
* 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));
}
}
}
