From the course: Machine Learning and AI Foundations: Classification Modeling

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Decision Trees

Decision Trees

From the course: Machine Learning and AI Foundations: Classification Modeling

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Decision Trees

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- [Instructor] Okay, decision trees. A big topic, also a popular topic because of all of the algorithms, decision trees are probably the most common. Why is it a complicated topic? Well, because decision trees are not one algorithm. There are many, and the way that they build, the execution is quite different for these different types. There are general principles though that we're able to explore that apply to all decision tree algorithms, but they truly are a family of techniques. They have a variety of missing data handling options, really quite different and different in interesting ways. However decision trees really are the exception to the rule. They do not use listwise deletion. They all have some alternative to that, either treating the missing data or setting the missing data side as if it was its own separate category. Also decision trees are a so-called greedy algorithm, meaning that as it's built, it's doing one variable at a time and will stop. If you've been listening…

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