What are the key parameters to tune in a random forest model?
An example of an AI chatbot conversation about tuning parameters in random forest models.
What are the key parameters to tune in a random forest model?
The key parameters to tune in a random forest model include the number of trees, maximum depth, and minimum samples split.
How does the number of trees affect the model's performance?
Increasing the number of trees generally improves performance but also increases computation time. It's a trade-off.
What is the default value for the maximum depth?
The default value for maximum depth is None, which means nodes are expanded until all leaves are pure or contain less than the minimum samples split.
Can you explain what 'minimum samples split' means?
'Minimum samples split' is the minimum number of samples required to split an internal node. It helps prevent overfitting.
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