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Add warning for hyperopt-parameters

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Matthias 2021-04-05 14:45:42 +02:00
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docs/hyperopt.md
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@ -305,6 +305,9 @@ There are four parameter types each suited for different purposes.
* `optimize` - when set to `False` parameter will not be included in optimization process. * `optimize` - when set to `False` parameter will not be included in optimization process.
Use these parameters to quickly prototype various ideas. Use these parameters to quickly prototype various ideas.
!!! Warning
Hyperoptable parameters cannot be used in `populate_indicators` - as hyperopt does not recalculate indicators for each epoch, so the starting value would be used in this case.
## Loss-functions ## Loss-functions
Each hyperparameter tuning requires a target. This is usually defined as a loss function (sometimes also called objective function), which should decrease for more desirable results, and increase for bad results. Each hyperparameter tuning requires a target. This is usually defined as a loss function (sometimes also called objective function), which should decrease for more desirable results, and increase for bad results.