Understanding Feature Engineering (Part 2) -- Categorical Data

We covered various feature engineering strategies for dealing with structured continuous numeric data in the previous article in this series. In this article, we will look at another type of structured data, which is discrete in nature and is popularly termed as categorical data. Dealing with numeric data is often easier than categorical data given that we do not have to deal with additional complexities of the semantics pertaining to each category value in any data attribute which is of a categorical type. We will use a hands-on approach to discuss several encoding schemes for dealing with categorical data and also a couple of popular techniques for dealing with large scale feature explosion, often known as the "curse of dimensionality". I'm sure by now you must realize the motivation and the importance of feature engineering, we do stress on the same in detail in'Part 1' of this series.