<figure><img src="../.gitbook/assets/image (170).png" alt="" width="211"><figcaption></figcaption></figure>

1. Click on _**GridSearch**_ under the _**Machine Learning**_ category.

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2. _**Model type**_: Select the type of machine learning model you want to use.

3. _**Scoring**_: Choose the metric for evaluating the model.

4. _**N jobs**_: Accelerate tasks through parallel processing. Enter the number of tasks to run simultaneously.

5. _**Cv**_: Specify the number of folds to be used during C_**ross-Validation**_.

6. _**Verbose**_: Display progress of the GridSearch. Higher values show more information.

7. _**Allocate to**_: Specify the variable name to allocate.

8. _**Param grid**_:

* _**Add param**_: Additional parameters other than 3 to 6 can be added.

* _**Add param set**_: Multiple combinations of parameters can be applied using sets.

9. _**Code view**_: Preview the generated code.

10. _**Run**_: Execute the code.