From the course: Machine Learning and AI Foundations: Classification Modeling
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Interactions
From the course: Machine Learning and AI Foundations: Classification Modeling
Interactions
- [Instructor] Interactions and interaction terms represent a big topic. But when I'm working with a model and I'm struggling to get better accuracy, this is one of the first places that I look. Interactions are when the relationship between two variables depends on a third. Since we're building predictive models, that's normally gonna take the form of our target variable, our binary, and one of our inputs being influenced by another input. Let's take a look at a couple of examples. So for instance here's an example from my regression course in the library. If we're trying to predict beginning salary using education level, we notice a general trend that as education level goes up, beginning salary goes up as well. But notice for the blue line which represents the men, the line goes up more steeply, and for the green line representing the women, the line goes up less steeply. So if we're really gonna understand the impact of education on beginning salary, we have to also know that…
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