Join Keith McCormick for an in-depth discussion in this video Lift Charts, part of Machine Learning and AI Foundations: Classification Modeling.
- [Instructor] A very popular way to visualize…modeling performance is a lift chart.…In fact, the whole concept of lift…is a popular way to assess models,…and there's all kinds of variations on this theme.…There's gains charts.…You can plot return on investment.…But we're gonna focus on lift.…So let's talk about how this is interpreted.…This plot is showing…relative risk…for diabetes.…And if we look at the left-hand side,…in particular, where I'm indicating,…we see that around the 15th percentile,…there's a group of folks whose diabetes risk…is almost eight times average.…
So let's say, for the sake of argument,…that we were gonna send out some outpatient care.…And these folks were gonna go to individuals' homes,…and we wanted to allocate that expensive resource…as efficiently as possible.…If we sent it out to 15% of patients,…that whole group of patients would represent elevated risk.…If we had a little bit more funding…and we could reach out to help more folks,…we could consider…sending folks out to everybody in the 20th percentile.…
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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