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Add warning for hyperopt-parameters
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@ -305,6 +305,9 @@ There are four parameter types each suited for different purposes.
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* `optimize` - when set to `False` parameter will not be included in optimization process.
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Use these parameters to quickly prototype various ideas.
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!!! Warning
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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.
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## Loss-functions
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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.
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