Exercise

Checking K-means assumptions

A very common issue in Machine Learning is applying a model without first checking whether your data meets the model's assumptions. By doing so, your analysis will likely arrive at some misleading conclusions.

In this exercise, you will be working with the mall data set, which contains 200 observations corresponding to mall customers characterized by means of three attributes: their age, annual income and spending score. You want to discover meaningful groups of customers and are excited to unleash the power of K-means on your data. Before doing that though, you are going to check whether your data meets K-means' assumptions or not.

The dplyr package has been loaded for you.

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Glimpse on the mall dataset.