How do I tune hyperparameters for my machine learning model?
An example of an AI chatbot conversation about tuning hyperparameters in machine learning models.
How do I tune hyperparameters for my machine learning model?
Tuning hyperparameters involves adjusting the settings of your model to improve performance. What model are you using?
I'm using a random forest classifier.
Great choice! You can tune hyperparameters like the number of trees, max depth, and min samples split. Would you like to know how to implement this?
Yes, please! How can I do that?
You can use techniques like Grid Search or Random Search with cross-validation to find the best hyperparameters. Would you like a code example?
That would be helpful, thank you!
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