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docs/guides/optimization/hyper-parameter-optimization/examples_hyperparam_opt.md
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@@ -2,7 +2,7 @@
title: Hyperparameter Optimization
---
The [hyper_parameter_optimizer.py](https://github.com/allegroai/clearml/blob/master/examples/optimization/hyper-parameter-optimization/hyper_parameter_optimizer.py)
The [hyper_parameter_optimizer.py](https://github.com/clearml/clearml/blob/master/examples/optimization/hyper-parameter-optimization/hyper_parameter_optimizer.py)
example script demonstrates hyperparameter optimization (HPO), which is automated by using ClearML.
## Set the Search Strategy for Optimization
@@ -24,7 +24,7 @@ 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, [`SearchStrategy`](https://github.com/allegroai/clearml/blob/master/clearml/automation/optimization.py#L310)
* Custom - Use a custom class and inherit from the ClearML automation base strategy class, [`SearchStrategy`](https://github.com/clearml/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.