Comments (5)
zer0n
commented on August 26, 2024
Next Step
After this, we will use hyperopt instead of random search.
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bischtob
commented on August 26, 2024
Could also incorporate Bayesian Optimization for hyperparameter search similar to what SigOpt does (https://sigopt.com/).
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zer0n
commented on August 26, 2024
hyperopt is a better alternative, open source, and popular. It's written by James Bergstra, also author of this paper. The algorithm behind hyperopt is TPE, which is described in that paper (section 4). The main issue with Bayesian Opt is that it only deals with continuous variables.
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bischtob
commented on August 26, 2024
Needs temporal cross-validation similar to this to feed into hyperopt:
https://robjhyndman.com/hyndsight/tscv/
https://robjhyndman.com/papers/cv-wp.pdf
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zer0n
commented on August 26, 2024
Go ahead
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Related Issues (20)
- Fix initializations when extending from Model
- Change code to pytorch HOT 2
- Specify the type of the variables for all functions
- Would be good if the user could provide a string as model
- Data dimensionality needs to be specified in the code HOT 1
- Getargspec is depracted. Please replace.
- github_total_push_events_2011-2018.csv wrongly named
- Split model module into encoder and decoder module HOT 1
- Add Stacked GRU for encoder architecture
- Parallel support for forecaster HOT 1
- Replace GitHub tutorial with a more detailed GefCom tutorial HOT 1
- Transforms need cleanup and more descriptions HOT 1
- Timeseries dataset object needs description and cleanup HOT 1
- make model checkpoint path variable HOT 1
- Explanation about value of input_channels parameter in the tutorial
- Implement distributed data parallel
- Support streaming dataset
- Kwargs in metrics need to be removed
- Need a custom losses module that can incorporate different kinds of losses
- Add custom loss function module
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