7. A server, comprising: means for applying machine learning techniques to generate a first family of classifier models using a boosted decision tree to describe a corpus of behavior vectors; means for computing an exclusive answer ratio for one or more nodes of the boosted decision tree; and means for determining which factors in the first family of classifier models have a high probability of enabling a mobile device to conclusively determine whether a mobile device behavior is not benign based on computed exclusive answer ratios.
7. A server, comprising: means for applying machine learning techniques to generate a first family of classifier models using a boosted decision tree to describe a corpus of behavior vectors; means for computing an exclusive answer ratio for one or more nodes of the boosted decision tree; and means for determining which factors in the first family of classifier models have a high probability of enabling a mobile device to conclusively determine whether a mobile device behavior is not benign based on computed exclusive answer ratios. 8. The server of claim 7 , wherein further comprising: means for applying the factors to the corpus of behavior vectors to generate a second family of classifier models that identify fewer data points as being relevant for enabling the mobile device to conclusively determine whether the mobile device behavior is not benign; and means for generating a mobile device classifier based on the second family of classifier models.