What's a best practice for Hyperopt workflow?
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06-23-2021 07:41 AM
- Choose what hyperparameters are reasonable to optimize
- Define broad ranges for each of the hyperparameters (including the default where applicable)
- Run a small number of trials
- Observe the results in an MLflow parallel coordinate plot and select the runs with lowest loss
- Move the range towards those higher/lower values when the best runs’ hyperparameter values are pushed against one end of a range
- Determine whether certain hyperparameter values cause fitting to take a long time (and avoid those values)
- Re-run with more trials
- Repeat until the best runs are comfortably within the given search bounds and none are taking excessive time
https://databricks.com/blog/2021/04/15/how-not-to-tune-your-model-with-hyperopt.html
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Best practice
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Long Time
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