Join Keith McCormick for an in-depth discussion in this video Discriminant with three categories, part of Machine Learning and AI Foundations: Classification Modeling.
- [Instructor] Okay, for our first algorithm…we're going to talk about linear discriminant analysis.…Now as the name implies, we're trying…to talk about the equation of a line,…but here we're focused on trying to separate two groups.…We want one group at one end of the line,…and another group at the other end of the line.…Now while we're discussing this,…we're gonna revisit a topic that…we talked about briefly earlier.…And that is that when we're trying…to predict into three categories,…it can complicate things more than we anticipate.…
So we'll start with two, but during this video…we're also gonna discuss the challenges…of trying to predict into three.…First, let's picture what we're trying to do.…We're looking at a data set that's actually a famous one…that's got the dimensions of petal width…and petal length for a group of flowers,…and we can imagine here that we could easily add a line…that trends through these data points.…Let's take a moment though to talk just a little bit…about the history of this famous data set.…
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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