Time Series Forecasting Using LSTM Networks: A Symbolic Approach

12 Mar 2020Steven ElsworthStefan Güttel

Machine learning methods trained on raw numerical time series data exhibit fundamental limitations such as a high sensitivity to the hyper parameters and even to the initialization of random weights. A combination of a recurrent neural network with a dimension-reducing symbolic representation is proposed and applied for the purpose of time series forecasting... (read more)

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