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Related Questions
- Can you explain the concept of overfitting and how random forests can help mitigate it in decision trees?
- How do ensemble methods like random forests combine the predictions of multiple decision trees to improve accuracy?
- In what ways do random forests reduce the variance of decision tree predictions, leading to more accurate results?
- How does the bootstrapping technique used in random forests help to improve the generalizability of decision tree models?
- What is the effect of feature randomization in random forests on the accuracy of decision tree predictions?
- Can you discuss the importance of hyperparameter tuning in random forests for achieving optimal accuracy in classification tasks?
- How do random forests handle missing values in the data, and what strategies are used to improve accuracy in such cases?
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