Databricks Machine Learning Associate Question 239
Single answerYou are tasked with training a machine learning model using Databricks AutoML to classify customer churn based on a dataset with 3 categorical features and 2 numerical features. One of the categorical features is a multi-class variable with 5 unique values. How many models will Databricks AutoML train by default if hyperparameter tuning is enabled?
- A
1 model
- B
5 models
- C
10 models
- D
Multiple models based on hyperparameter tuning
Show answer and explanation
Correct answer: D
Explanation
Databricks AutoML trains multiple models when hyperparameter tuning is enabled. The number of models depends on the hyperparameter search space, which is automatically defined by Databricks AutoML. The search space considers the type of model and dataset characteristics, iterating through different model configurations to optimize performance.
- A. Incorrect.
This option is incorrect. Databricks AutoML trains more than one model when hyperparameter tuning is enabled.
- B. Incorrect.
This option is incorrect. The presence of a multi-class categorical variable does not mean one model is trained per class; hyperparameter tuning involves training multiple models.
- C. Incorrect.
This option is incorrect. Databricks AutoML does not train a specific fixed number of models like 10 by default; the number of models depends on the hyperparameter search space.
- D. Correct.
This option is correct. When hyperparameter tuning is enabled, Databricks AutoML trains multiple models using its automated search process to identify the best configuration.