Successive Halving Iterations

# Introduction In this lab, you will learn how to use the successive halving search method to iteratively choose the best parameter combination out of multiple candidates. This method is implemented in `HalvingGridSearchCV` and `HalvingRandomSearchCV` classes from the Scikit-learn library. The `HalvingRandomSearchCV` class will be used in this lab. ## VM Tips After the VM startup is done, click the top left corner to switch to the **Notebook** tab to access Jupyter Notebook for practice. Sometimes, you may need to wait a few seconds for Jupyter Notebook to finish loading. The validation of operations cannot be automated because of limitations in Jupyter Notebook. If you face issues during learning, feel free to ask Labby. Provide feedback after the session, and we will promptly resolve the problem for you.

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