Comments (2)
@Daisy8po I'm not sure exactly what you mean by that. Can you detail a bit more, maybe give a concrete example with numbers?
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The TCN layer input/output work exactly like an LSTM. If your X is multivariable and your Y univariate, you're looking at a Many-To-One regression problem. You can google "Keras LSTM many to one regression". And in any tutorial you can swap the LSTM class by the TCN class and it should work seamlessly.
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Related Issues (20)
- setup.py requirements on mac os HOT 7
- How do I use a masking layer for TCN? I want to mask certain time steps which are missing. HOT 4
- ValueError: Unknown layer: TCN when trying to load saved model HOT 3
- Dilations and nb_stack relationship HOT 4
- The parameter of the TCN HOT 7
- Masking time steps in order to use TCN for variable length sequences HOT 2
- data shape of tcn layer HOT 1
- help one regression per sequence HOT 1
- Ensuring unique weights when a model uses multiple TCNs HOT 2
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- How can i use TCN to build seq2seq model? HOT 1
- keras-tcn for R HOT 2
- Visualization of internal structure of TCN block HOT 1
- Low accuracy in keras-tuner based TCN model for audio classification HOT 6
- Saving a loaded model gets warning and then fails to open HOT 1
- exchange_rate.txt HOT 5
- Question: Skip connections HOT 2
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- Confusion about regression or classification head
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