From the course: Machine Learning and AI Foundations: Clustering and Association
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Running hierarchical cluster analysis
From the course: Machine Learning and AI Foundations: Clustering and Association
Running hierarchical cluster analysis
- [Instructor] We're going to walk through the menus for running a hierarchical cluster analysis. Now remember, hierarchical cluster analysis is very computationally intensive. You can only use it on small data sets. So we're in ReadyForCluster GT60 Trans, which has just 34 cases in it. Analyze, Classify, Hierarchical, and here we go. Now also remember that we have two versions of the variables in here. We have the sums and the ratios. The ratios are there because they've been standardized. So let me show you something in the menus. If you go to Method, you can actually see that this menu will allow you to transform your original variables in a number of different ways. You can transform them to use Z-scores, which means that the average is zero, a plus one is one standard deviation above the mean, and a minus one is one standard deviation below the mean, and you can see numerous other choices that you have. Now, note as well that if you choose to standardize here, you can standardize…
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