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(c.) Describe how overfitting is addressed within a nearest neighbour classification approach? (d) How can ensemble learning (e.g. random forests) help address overfitting? (e) What

(c.) Describe how overfitting is addressed within a nearest neighbour classification approach? (d) How can ensemble learning (e.g. random forests) help address overfitting? (e) What is cross-validation and how does it work? (f). How does cross validation help to prevent over-fitting?

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