Join Keith McCormick for an in-depth discussion in this video Decision Trees, part of Machine Learning and AI Foundations: Classification Modeling.
- [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 carefully, you may have noticed…
Note: These tutorials are focused on the theory and practical application of binary classification algorithms. No software is required to follow along with the course.
- Why do you need classification?
- Statistical algorithms versus machine learning algorithms
- Combining models using ensembles
- Classification modeling challenges
Skill Level Intermediate
SPSS Statistics Essential Trainingwith Barton Poulson4h 57m Beginner
Machine Learning and AI Foundations: Recommendationswith Adam Geitgey58m 7s Intermediate
1. The Big Picture: Defining Your Classification Strategy
2. How Do I Choose a "Winner"?
3. Algorithms on Parade
4. Common Modeling Challenges
Next steps3m 17s
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