EAST representation: fast discovery of discriminant temporal patterns from time series
Résumé
Mining discriminant temporal patterns is one problematic for the time series classification currently led by the shapelet. We expose this problematic under the angle of a standard feature-space classification task. This approach is enabled by the recent observation that most enumerable subsequences from a time series are redundant and can be discarded. In addition to be simple, the approach turns out to have state of-the-art classification performances with extremely fast computations. It also provides a flexible framework with interesting perspectives.