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run_train infinite loop?
See original GitHub issueHi,
First of all, congrats for this project, it appears to be very promising.
I ran run_train like this ./run_train.py --target=low BTC_ETH --period=day and 2 days later, it’s still running with around 77 _zoo/BTC_ETH sub folders, with only LinearModel.
Could it be the reason that the training is still ongoing? i.e. in an attempt to find other models with good results, without success? I did not find where to configure the limit.
Thanks and keep the good work!
Issue Analytics
- State:
- Created 5 years ago
- Comments:6 (3 by maintainers)
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@bautroibaola This is a common problem in ML: there is no way to tell the model is ready. What people usually do is train it as long as they have time and simply take the best models. That’s why there’s an endless loop. However, feel free to replace it with some limit.
Dear maxim,
I also have same concern with flamby:
Because in run_train.py has while True loop, so how can I know when I should stop the training and move to run_predict.py? And need I run train every time before run predict?
Thanks for your hard work!