A finance company wants to analyze sequences of stock prices to predict future market movements. Given the long sequences of data, which RNN variant would be more suited to capture potential long-term dependencies in the data?
- Simple RNN
- Bidirectional RNN
- Gated Recurrent Unit (GRU)
- Long Short-Term Memory (LSTM)
A Long Short-Term Memory (LSTM) is a suitable choice for capturing long-term dependencies in stock price sequences. LSTM's memory cell and gating mechanisms make it capable of handling long sequences and understanding potential trends in financial data.
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