How can I optimize hyperparameters in my sklearn model?
An example of an AI chatbot conversation about tuning hyperparameters in sklearn models.
How can I optimize hyperparameters in my sklearn model?
You can use techniques like Grid Search or Random Search to optimize hyperparameters in your sklearn model.
Can you explain how Grid Search works?
Grid Search exhaustively searches through a specified subset of hyperparameters, evaluating model performance for each combination.
What about Random Search? Is it better than Grid Search?
Random Search samples a fixed number of hyperparameter combinations randomly, which can be more efficient than Grid Search in high-dimensional spaces.
How do I implement Grid Search in my code?
You can use GridSearchCV from sklearn.model_selection. Just pass your model, parameter grid, and scoring method.
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