La Hierarchical clustering - HAC
After three courses so far, we've seen the three main factor analysis methods: principal components analysis, correspondence analysis, and multiple correspondence analysis. These three methods can be applied in numerous applications, to many types of data table.
On this course, we're going to have a look at a slightly different method: clustering. This method can be applied to all of the types of table we've seen so far, and also can be used to extract further information from the data, as a complement to the factor analysis methods we've seen so far.
Hierarchical clustering aims to organize statistical individuals based on their similarity, either by a hierarchical tree or by forming clusters of individuals.
Course and sofware implementation
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The exercise
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