From the course: R Essential Training Part 2: Modeling Data

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Creating ensemble models with random forest classification

Creating ensemble models with random forest classification

From the course: R Essential Training Part 2: Modeling Data

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Creating ensemble models with random forest classification

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- [Instructor] In our final demonstration of working in R to analyze and declassify data, I want to show you how to do something called a random forest. Now, in a previous video, I talked about decision trees, where you take your data and you have a whole series of yes, no decisions that split it off into these branches until you have a final model and it's able to portray it graphically which is wonderful. A random forest is essentially a large collection of decision trees. It's also an introduction into what's known as ensemble modeling. And what that is, instead of having just one model, use the wisdom of the crowds, you know, the idea that two heads are better than one, use many models and combine them because, typically, the averaged predictions of several different models are going to be more accurate than the predictions of any one model. Now to show you how this works, I'm going to load a few packages, including…

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