Summary

This chapter covered the basics of data cleanup and dimensionality reduction. After reading it, you should understand how to work with missing values, rescale input data, and handle categorical variables. You should also understand the troubles of having high-dimensional data and how to combat it with feature reduction techniques including filter, wrapper, and transformation methods.

In the next chapter, we will cover clustering and other ways in which to group records for data mining insights.