I've been exploring methods for encoding categorical data. I was hoping to find a good method that does not increase the dimension of the dataset, similar to the one used on this dataset about drug use: Drug consumption (quantified) Data Set
Each piece of categorical data in this dataset was converted to some real number, but yet the dimension of the dataset was not increased. Instead of just randomly replacing values with numbers, there appears to be some thought out method behind this. Can anyone shed some light on this matter?