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Related Questions
- What are the key differences between random search and grid search for hyperparameter tuning in machine learning?
- How does random search reduce the computational cost compared to grid search?
- What are the scenarios where grid search is preferred over random search for hyperparameter tuning?
- Can random search be used for categorical hyperparameters, and if so, how?
- How does the number of iterations in random search affect the quality of the results?
- Can random search be used in conjunction with other optimization techniques, such as Bayesian optimization?
- What are the trade-offs between random search and grid search in terms of exploration-exploitation balance?
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