ClassificationEvaluator ce = new ClassificationEvaluator();
if(false) {
ce = new ClassificationEvaluator();
DecisionTree dt = new DecisionTree(bagEvents);
dt.printTree();
for(int i=0;i<testBagEvents.size();i++) {
BagEvent be = testBagEvents.get(i);
String result = dt.testBag(be.getFeatures());
ce.logEvent(be.getClassLabel(), result);
}
System.out.println(ce.getAccuracy());
System.out.println(ce.getKappa());
ce.pprintConfusionMatrix();