I am trying to understand this XGboost example.
ptrain = bst.predict(dtrain, output_margin=True)
they make prediction on test data, but the problem is the test data already has all the label. If my test data only has features and no label, how can I modify that example to make prediction?
Also, what I observe from their datasets:
agaricus.txt.test is that they do not need to have the same features, and even each training data has different features. I have done linear regression before, I thought training and test datasets should have the same set of features?