How does the Random Forest algorithm handle the issue of overfitting seen in individual decision trees?
- By aggregating predictions from multiple trees
- By increasing the tree depth
- By reducing the number of features
- By using a smaller number of trees
Random Forest handles overfitting by aggregating predictions from multiple decision trees. This ensemble method combines the results from different trees, reducing the impact of individual overfitting.
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