DMIDAS: Deep Mixed Data Sampling Regression for Long Multi-Horizon Time Series Forecasting

no code implementations • 7 Jun 2021 • Cristian Challu, Kin G. Olivares, Gus Welter, Artur Dubrawski

We validate our proposed method, DMIDAS, on high-frequency healthcare and electricity price data with long forecasting horizons (~1000 timestamps) where we improve the prediction accuracy by 5% over state-of-the-art models, reducing the number of parameters of NBEATS by nearly 70%.

regression Time Series +1