Real world datasets often contain categorical attributes. Some models support these natively (e.g. decision trees), but others have to be modified somehow to support them. This post focuses on techniques that can be used to convert categorical attributes into continuous ones so they might be used with those models that don’t support categorical attributes well natively (like neural networks).