I have a data-set with 14~ attributes, roughly half of them nominal. I've used a binary vectorizer to convert these values to a number of attributes. The number of attributes, naturally, ballooned up; I'm sitting on roughly 50 at the moment. I've looked at using PCA to reduce this number.
As far as I can understand the things I've been reading, I should exclude my target variable from the analysis. But I'm not sure if I should perform PCA on the whole remaining data set (Including the values that were already numerical, like 'age') or just on the values I converted from Nominal to Numerical and then re-add those to the already numeric values.
To clarify, I've already converted this data-set from nominal to binary, and I'm not sure if I should apply PCA to just the binary columns generated, or the entire thing.