KDD and CRISP-DM are both processes to structure your Data Mining procedure. Is data labeling not also a important part of Data Mining?
Data labeling is for example in unsupervised learning the target of the Data Mining process. So if I want to classify a data set that was labelled by me before, do I just do the process twice? In my opinion sometimes the labeling is quite trivial, so that doing the process twice would be quite unnecessary?
Is it possible to include the labeling into the data exploring or preprocessing phase? E.g. in CRISP-DM Preprocessing there is something like generating a new parameter. Can this Parameter be also a new target/label?
I know this question is quite process orientated and in Data Mining you are quite free but just assume that in this case you have to follow the process.