What are the best practices for parameter selection in machine learning?
An example of an AI chatbot conversation about best practices for selecting parameters in ML models.
What are the best practices for parameter selection in machine learning?
The best practices include using cross-validation, grid search, and understanding the model's sensitivity to parameters.
Can you explain how cross-validation helps in parameter selection?
Cross-validation helps by dividing the dataset into training and validation sets, allowing you to assess how well your model generalizes.
What is grid search and how does it work?
Grid search is a technique that exhaustively searches through a specified subset of hyperparameters to find the best combination.
Are there any automated tools for parameter selection?
Yes, tools like Optuna and Hyperopt can automate the process of hyperparameter optimization.
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