Reliable early classification of time series

Abstract

Early classification of time series is important in time-sensitive applications. An approach is presented for early classification using generative classifiers with the dual objectives of providing a class label as early as possible while guaranteeing with high probability that the early class matches the class that would be assigned to a longer time series. We give a specific algorithm for early quadratic discriminant analysis (QDA), and demonstrate that this classifier meets the requirement of reliable early classification.