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pollfly
2023-11-15 12:11:28 +02:00
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docs/guides/optimization/hyper-parameter-optimization/examples_hyperparam_opt.md
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@@ -24,14 +24,14 @@ The following search strategies can be used:
* Random uniform sampling of hyperparameter strategy - [automation.RandomSearch](../../../references/sdk/hpo_optimization_randomsearch.md)
* Full grid sampling strategy of every hyperparameter combination - [automation.GridSearch](../../../references/sdk/hpo_optimization_gridsearch.md).
* Custom - Use a custom class and inherit from the ClearML automation base strategy class, automation.optimization.SearchStrategy.
* Custom - Use a custom class and inherit from the ClearML automation base strategy class, [SearchStrategy](https://github.com/allegroai/clearml/blob/master/clearml/automation/optimization.py#L310)
The search strategy class that is chosen will be passed to the [automation.HyperParameterOptimizer](../../../references/sdk/hpo_optimization_hyperparameteroptimizer.md)
object later.
The example code attempts to import `OptimizerOptuna` for the search strategy. If `clearml.automation.optuna` is not
installed, it attempts to import `OptimizerBOHB`. If `clearml.automation.hpbandster` is not installed, it uses
the `RandomSearch` for the search strategy.
`RandomSearch` as the search strategy.
```python
try: