Concept drift due to hidden changes in context complicates learning in many domains including nancial prediction, medical diagnosis, and communication network performance. Existing machine learning approaches to this problem use an incremental learning, on-line paradigm. Batch, oo-line learners tend to be ineeective in domains with hidden changes in context as they assume that the training set ...