Time-Series Classification for Dynamic Strategies in Multi-Step Forecasting

Multi-step forecasting (MSF) in time-series, the ability to make predictions multiple time steps into the future, is fundamental to almost all temporal domains. To make such forecasts, one must assume the recursive complexity of the temporal dynamics. Such assumptions are referred to as the forecasting strategy used to train a predictive model. Previous work shows that it is not clear which forecasting strategy is optimal a priori to evaluating on unseen data. Furthermore, current approaches to MSF use a single …

assumptions classification complexity cs.ai cs.lg domains dynamic dynamics forecasting future multiple predictions predictive recursive series strategies strategy temporal train