Describe the role of hyperparameter tuning in the performance of a Machine Learning model.
- It adjusts the weights during training
- It optimizes the model's parameters before training
- It optimizes the values of hyperparameters to improve the model's performance
- It selects the type of model to be used
Hyperparameter tuning involves optimizing the values of hyperparameters (parameters set before training) to improve the model's performance. It helps in finding the best combination of hyperparameters that provides optimal performance for a given dataset.
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