public AdaptiveMartiBoost(String trainData, String holdoutData, int levels) throws Exception {
this.numLevels = levels;
Instances trainInstances = WekaUtil.getInstances(trainData);
Instances holdoutInstances = WekaUtil.getInstances(holdoutData);
AdaptiveMartiNodeFactory.setInstances(trainInstances);
rootLevel = new AdaptiveMartiLevel(0);
rootLevel.addNode(new AdaptiveMartiNode(trainInstances, holdoutInstances, rootLevel, 0));
// rootLevel.build();
// root.display();
gb_matrix = new ConfusionMatrix();
LOGGER.log(Level.INFO, "Initial global conf matrix :");
gb_matrix.display();
}
public void evaluateTestData(String testFile) throws Exception {
rootLevel.getNodes().get(0).getInData().setTestInstances(WekaUtil.getInstances(testFile));
AdaptiveMartiLevel currentLevel = rootLevel;
while (currentLevel.getLevelNumber() < numLevels) {
System.out.println("Level " + currentLevel.getLevelNumber());
if (currentLevel.getLevelNumber() == numLevels - 1) currentLevel.setFinalLevel(true);
currentLevel.classifyRouteTestInstances(gb_matrix);
currentLevel = currentLevel.getNextLevel();
}
gb_matrix.display();
}