From the course: Machine Learning and AI Foundations: Clustering and Association

Unlock the full course today

Join today to access over 22,600 courses taught by industry experts or purchase this course individually.

Running a multiple correspondence analysis

Running a multiple correspondence analysis

From the course: Machine Learning and AI Foundations: Clustering and Association

Start my 1-month free trial

Running a multiple correspondence analysis

“

- [Instructor] I want to introduce you to what's a really amazing technique. It's probably new to you, and it's possible that you haven't heard of it. It's called multiple correspondence analysis. So, the reason that it belongs in this course is it's a powerful way to look at a group of categorical variables. This might be surprising, because we've been talking about scale variables throughout most of this cluster analysis course, but what we're going to do is we're going to take the KMeans cluster analysis solution, which upon solution is a categorical variable, and then relate it to potentially several of our other categorical variables. Now, to make this work, you're going to want to identify those categorical variables that seem to be related to your cluster membership variable. So please do cross tabulations or Pearson chi-square, or something like that in preparation for this. But I've identified some variables that will be interesting to bounce off our KMeans membership…

Contents