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When did your smartphone bother you last?

This paper is prompted by the overall question 'what is the most effective way to recognise disruptive smartphone interruptions?'. We design our experiments to answer 3 questions: 'Do users revise what they perceive as disruptive incoming calls as time goes by?', 'How do different types of machine-learners (lazy, eager, evolutionary, ensemble) perform on this task?' and 'Can we restrict the initial amount of data and/or the number of features we need to make predictions without degrading performance?'. We consider these questions using Cambridge University's Device Analyzer dataset.