Databricks Certified Machine Learning - Associate

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In the context of AutoML, explain the role of model selection and how AutoML can automate this process. Provide a detailed description of the techniques used by AutoML for model selection and their significance in improving model performance.

Simulated

Model selection is not necessary in AutoML, as the algorithm automatically selects the best model based on the dataset.

6.9%

Model selection is important in AutoML, but it is performed manually by the user by trying different models and selecting the best one based on their performance.

6.9%

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Model selection is important in AutoML, and it can be automated using techniques such as ensembling, stacking, and model blending to combine the predictions of multiple models and improve the overall performance.

27.6%

Model selection is important in AutoML, and it can be automated by training multiple models on the dataset and selecting the one with the highest evaluation metric score.

58.6%