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Related Questions
- What is the term for the problem of dealing with a large number of hyperparameters in machine learning?
- How does the curse of dimensionality affect the computational time of a grid search in hyperparameter tuning?
- What is the main reason why grid search becomes impractical for large numbers of hyperparameters?
- Can you give an example of a scenario where a large number of categorical hyperparameters makes grid search computationally expensive?
- How does the number of possible combinations in a grid search increase with the number of hyperparameters?
- What is an alternative approach to grid search that can handle a large number of hyperparameters?
- Can you describe a real-world scenario where a large number of hyperparameters led to an impractically long computational time for grid search?
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