Measuring performance of different classifiers without class type in data
Normal classification will not work in this case, classifiers learn functions that are able to seperate the training examples. In your case you only have one class which will not work for all the classical examples. There is a machine learning task called One-class classification, see this Wikipedia page. In your case PU Learning (Positive and Unlabeled) seems most appropriate. Evaluating the performance is extremely difficult without having some negative examples as well however. See this question and answer on the Stats stackexchange.