Conceptual question. Imagine I wished to conduct a three-stage classification and prediction procedure:
Stage (1): Use an unsupervised method (whether k-modes, PAM, latent class, whatever) on a subset of Likert-scale categorical variables to classify/cluster these.
Stage (2): Store the class/cluster output.
Stage (3): Use the unsupervised output as a dependent (ordinal or otherwise) variable in a supervised routine. Thus, evaluate whether baseline characteristic variables (age, sex, etc) could sufficiently predict outcome previously obtained the Stage (1)-(2).
This is what I endeavour to do. However, I am not sure if anyone has seen this type of process before? If it has a formal name? And if there are any useful links to papers/code in R?
Would appreciate the feedback