Comments (3)
Hi @camerons1967,
We would recommend you to try this in a Google Colab, it is a lot faster. Here is a link to the ETT's replication.
Eventually hyperopt
bayesian optimization can still stuck in bad local optimas, so you need to increase the number of hyperparameter exploration steps.
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Hi,
I've tried to work with the notebook and the code. The notebook reproduces the results, but the code doesn't.
What is the reason for this issue? Is there something missing in the repository?
Thanks!
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Hi @omerlux,
We conducted all of our experiments in GPUs (a lot faster). An explanation is that initialization of the network's parameters and rounding differ between GPUs and CPUs.
Nevertheless N-HiTS should be able to achieve similar results on the CPU if you let the hyperparameter optimization algorithm run for longer to escape bad local optimas.
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Related Issues (15)
- About your data processing + final result HOT 2
- Follow up to "change-in-level" forecast
- I can't see the model's detail in the code HOT 7
- I am confuse about this line : n_theta = (input_size + max(h//n_freq_downsample[i], 1) ) HOT 1
- /
- How to make multivariate forecasting?
- Is backcast interpolated?
- About training procedures and doc HOT 2
- Clarification regarding data pre-processing HOT 2
- different settings (nhits vs. autoformer) HOT 2
- Clarification regarding data normalization
- what is the file 'hyperopt' ? HOT 1
- Clarification regarding implementation HOT 1
- Question on n_time_in HOT 1
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