Pre-processing mixed data prior to clustering I am new to hierarchical clustering, and wish to perform clustering on mixed data. I am slightly confused on the necessary pre-processing steps. I understand how to pre-process purely continuous data, what I haven't been able to identify is what pre-processing steps are necessary for mixed data? Do I just scale my continuous variables, impute missing data, and leave the categorical variables alone? Or do I need to perform transformations across all of my variable types?
If it's categorical you can use the presence/absence of each category as a feature.  

If it's nominal (ordered) you can normalize their values to be between 0 and 1 (or whatever range you normalized the rest of your data to).