AbstractOutput classificationOutput = null;
if (forPredictionsPrinting.length > 0) {
// print the header first
classificationOutput = (AbstractOutput) forPredictionsPrinting[0];
classificationOutput.setHeader(data);
classificationOutput.printHeader();
}
// Do the folds
for (int i = 0; i < numFolds; i++) {
Instances train = data.trainCV(numFolds, i, random);