Join Keith McCormick for an in-depth discussion in this video Logistic regression, part of Machine Learning and AI Foundations: Classification Modeling.
- Okay, let's talk about logistic regression.…You're gonna notice some similarities in look and feel…from logistic regression and discriminate analysis,…particularly at the level of detail,…but once we get to the other algorithms,…you're gonna notice a striking difference…between logistic and discriminate on the one hand,…and all of the others, because these are really the two…that come from the statistics tradition.…First, note that like many of the algorithms,…virtually all, in fact, logistic operates…by listwise deletion, meaning that…if any data's missing, that row is eliminated.…
All inputs are used unless you…choose to do stepwise logistic.…So, like discriminate, we have a stepwise option.…Have to use scale variables.…In practice, however, when epidemiologists,…health researchers, use logistic regression,…they tend to have mostly categorical variables,…so we can employ dummy coding,…and dummy coding is very common…in logistic regression models.…Logistic is arguably the most transparent of all the models.…
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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