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Understanding random forests

Groups of classification trees can be combined into an ensemble that generates a single prediction by allowing the trees to "vote" on the outcome.

Why might someone think that this could result in more accurate predictions than a single tree?

This exercise is part of the course

Supervised Learning in R: Classification

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