Databricks Machine Learning Associate Question 574
Select 3You are training a machine learning model in Databricks and want to optimize its hyperparameters. You decide to use grid search to find the best combination of hyperparameters for your model. Which of the following statements about grid search are true?
- A
Grid search systematically evaluates all possible combinations of hyperparameter values within the specified search space.
- B
Grid search is computationally efficient compared to random search for large hyperparameter spaces.
- C
Grid search can be parallelized in Databricks to speed up the hyperparameter tuning process.
- D
Grid search is effective when the number of hyperparameters and their possible values is small.
- E
Grid search uses a probabilistic approach to explore the hyperparameter space.
Show answer and explanation
Correct answers: A, C, D
Explanation
Grid search is a brute-force hyperparameter tuning method that systematically evaluates all possible combinations of hyperparameters in the specified search space. While it is effective for small hyperparameter spaces, it can become computationally expensive for larger spaces. In Databricks, grid search can be parallelized to speed up the process. However, it does not employ probabilistic methods, unlike Bayesian search or random search.
- A. Correct.
Correct: Grid search systematically evaluates all possible combinations of hyperparameter values within the specified search space, making it a brute-force method for tuning.
- B. Incorrect.
Incorrect: Grid search is computationally expensive, especially for large hyperparameter spaces, as it evaluates every combination exhaustively, unlike random search.
- C. Correct.
Correct: Grid search can be parallelized in Databricks using tools like MLlib or Hyperopt to distribute the workload and reduce computation time.
- D. Correct.
Correct: Grid search is effective when the hyperparameter space is small because it evaluates all combinations, which becomes impractical for large spaces.
- E. Incorrect.
Incorrect: Grid search does not use a probabilistic approach; it deterministically explores all combinations of the search space.