Time Series Forecasting, Classification, Deep Learning, Recurrent Neural Network, Missing Data.
learning. Conclusion It is quite challenging to deal with missing values in time series datasets and use Recurrent Neural Networks to deal with them. This article proposed a new architecture based on Gated Recurrent Units (GRUs) with some modifications which outperformed on time-series datasets