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Related Questions
- What is the main difference in computational cost between grid search and random search for hyperparameter tuning?
- How does the number of hyperparameters and their range affect the computational cost of grid search versus random search?
- In what scenarios is grid search more efficient than random search, and vice versa?
- Can you explain the concept of 'optimism' in random search and how it impacts its computational cost?
- How does the use of Bayesian optimization compare to grid search and random search in terms of computational cost and efficiency?
- What are some strategies to reduce the computational cost of grid search and random search for large-scale hyperparameter tuning?
- Can you discuss the trade-off between exploration and exploitation in random search and how it affects its computational cost?
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