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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