What are the main differences between GridSearchCV and RandomizedSearchCV?
GridSearchCV exhaustively searches through a specified parameter grid, while RandomizedSearchCV samples a fixed number of parameter settings from the specified distributions.
Which one is more efficient for large datasets?
RandomizedSearchCV is generally more efficient for large datasets because it doesn't evaluate all combinations, saving time.
Can you give an example of when to use each?
Use GridSearchCV when you have a small parameter space and need precise tuning. Use RandomizedSearchCV for larger spaces where you want a good solution quickly.
Are there any drawbacks to using RandomizedSearchCV?
Yes, the main drawback is that it may miss the optimal parameter combination since it samples randomly.
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