How does the bagging technique reduce the variance in a model?
- By averaging the predictions of multiple models trained on different subsets of data
- By focusing on the mean prediction
- By increasing complexity
- By reducing the number of features
Bagging reduces variance by averaging the predictions of multiple models, each trained on a different random subset of the data (with replacement). This averaging process smooths out individual variations, leading to a more stable and robust model.
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