You can optimize hyper-parameters to improve the performance of your models.

Hyper-Parameter Optimizer Dialog

When you click the HPO button in the Pipeline Parameters panel, the Hyper-Parameter Optimizer dialog is displayed.

The Hyper-Parameter Optimizer dialog layout is shown in the image below.

You can enter information for Hyper-Parameter Optimization in the Settings Panel, and check the results in the Result Panel. Moreover, you can check the state of the Hyper-Parameter Optimizer above the Result Panel.

The state is classified into 5 different states.

Ready, Running, Stopped, Failed, Completed

Enter Information for Hyper-Parameter Optimizer

To optimize the hyper-parameters, enter the necessary information in the settings panel.

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To activate the Run button, you must enter all items in Settings Panel except Early Stopping Rounds.

Your input is not saved after you click the Close button.


Target Component	Select the component with the target you want to optimize.
Target Expression	The last expression of a target component is automatically selected as the target.
Target	The Target Expression displays all target values.
Sampler	Select one sampler(tuning method) among Bayesian, Grid Search, and Random Search.
Type	Assign a type to each target. Choose Min if you want to minimize the target value and Max if you want to maximize it.
Iterations	Enter the number of iterations.
Early Stopping Rounds	(Optional) Set the number of iterations to stop optimization after a target value no longer needs optimization.
Pipeline Parameters	Select one or more pipeline parameters. And enter a Range and choose Distribution for all selected pipeline parameters. - Range : Enter a range of the target value. - Distribution : Choose a distribution among Discrete Uniform, Float, Int, Loguniform, or Uniform. - Interval : Enter Interval instead of selecting Distribution if Grid Search is selected as Sampler.

Run Hyper-Parameter Optimizer and Apply Results

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If Run is clicked, the hyper-parameter optimization will run from the beginning, regardless of the Ready/Completed/Stopped/Failed status.

It may be necessary to select one of the Best Trials before clicking Apply if you have multiple Target Values.

hpo-multiple-edited (1)

Click the Run button to run the Hyper-Parameter Optimizer.
As executions take place, you can view the target value changing in real time in the Graph and Log tabs in the Result Panel.
1. Iteration Graph: A real-time graph of target values based on the number of executions
2. Log Table: A real-time table of target and parameter values based on the number of executions
3. Parameter Importance: A graph illustrating the relative importance of pipeline parameters (available only when there are two or more parameters)
4. Pareto Front Plot: Graphical representation of the target values (available only when there are two or three target values)
After the hyper-parameter optimization is complete, apply the optimized value by clicking Apply.