Practical Predictive Analytics

Preparing the data for analysis

We will first perform some data preparation in order to normalize the data for k-means. Normalization is pretty much a requirement for k-means, since it forces each variable to be scale-independent so that measuring distances between the k-means clusters is also scale-independent.

Recall that one way to normalize a variable is to first obtain the mean of the variable and then divide by its standard deviation.