17 Using predictions to make more predictions
This chapter covers
- Examining the autoregressive LSTM (ARLSTM) architecture
- Discovering the caveat of the ARLSTM
- Implementing an ARLSTM
In the last chapter, we examined and built a convolutional neural network (CNN). We even combined it with the LSTM architecture to test whether we could outperform the LSTM models. The results were mixed, as the CNN models performed worse as single-step models, performed best as multi-step models, and performed equally well as multi-output models.
Now we’ll focus entirely on the multi-step models, as all of them output the entire sequence of predictions in a single shot. We’re going to modify that behavior and gradually output the prediction sequence, using past ...
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