From the course: Machine Learning & AI Foundations: Linear Regression
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Categorical regression with optimal scaling - SPSS Tutorial
From the course: Machine Learning & AI Foundations: Linear Regression
Categorical regression with optimal scaling
- [Instructor] Okay, so we know that regression is all about predicting a scale variable with one or more scale variables. Well, somewhat obviously, we don't always have scale variables, so then what do we do? Well, we're going to go ahead and take a look at a technique called categorical regression, and to do so, we're going to use a data set that is found in the Additional Data Files folder called Satisfaction. Okay, well, here's the Satisfaction data set, and we can see that our dependent variable Recommend is nominal in nature. Some folks answered yes, some folks answered no, and some folks answered don't know. We're going to actually include the don't know. If we only had yes, no, we could consider something like binary logistic regression, but since we do want to include the don't know, we really have to treat our dependent as a nominal variable. So let's take a look. We're going to find the technique that we need in the Regression folder, and then down here, where it's called…
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Contents
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Regression options5m 20s
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Automatic linear modeling6m 37s
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Regression trees6m 19s
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Time series forecasting4m 30s
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Categorical regression with optimal scaling6m 9s
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Comparing regression to Neural Nets4m 31s
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Logistic regression4m 54s
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SEM4m 23s
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