How does hyperparameter tuning influence the performance of a classification model?
- Enhances model performance by fine-tuning algorithm parameters
- Increases computational time but doesn't affect performance
- Makes the model simpler
- No influence
Hyperparameter tuning involves finding the optimal hyperparameters (e.g., learning rate, regularization strength) for a given model and data. This fine-tuning process helps in enhancing the model's performance by finding the best configuration for the learning algorithm.
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