I have conducted PCA that has reduced the dimensions of my data from more than 20 to 7 (7 PCAs explain about 85% of the total variation). As a second step, I have to cluster my data based on these new 7 PCAs.
My question is: how I should reconstruct/transform my data (cbind/rbind)? As I understand, each PCA is a weighted mix of the original variables. So should I just replace the old variables with the PCAs?
Also, how should I interpret the final results? If there was no PCA, each cluster would incorporate all variables in some proportion. But after PCA, how would I describe each cluster? For instance, cluster 1 contains 40% of PCA 1 and PCA 1, in turn, has xxx loading scores? Something like this? Would greatly appreciate any help on interpreting this.