From the course: R Essential Training Part 2: Modeling Data
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Classifying cases with decision tree analysis
From the course: R Essential Training Part 2: Modeling Data
Classifying cases with decision tree analysis
- When you're working with data, sometimes you're building a model that your algorithm is going to implement directly on its own, like a recommendation engine on a eCommerce website. But in many other circumstances, if you're building a model for a humans, they actually need to be able to understand what's happening and given that humans are visual animals, a graphic that can portray the entire model as priceless. And that's one of the things I love about decision trees. You get the entire model with a picture, a series of yes/no decisions. And I'm want to show you how this works in R. We're going to start by learning a few packages including caret which is used for a number of predictive analysis, and rattle which allows me to produce a slightly prettier and more informative graphic for a decision tree. So let's load those packages. And then I'm going to come down and use the big five data set that we've used in other…
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Contents
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Grouping cases with hierarchical clustering10m 58s
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Grouping cases with k-means clustering7m 54s
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Classifying cases with k-nearest neighbors11m 57s
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Classifying cases with decision tree analysis9m 13s
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Creating ensemble models with random forest classification9m 20s
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