An unsupervised classification approach is improved by imposing some order into the treatment of the records and their attributes, which otherwise would be treated as random variables. A method is provided to identify particular attributes that are most associated with the “good” records within each of the plurality of groups of records within a data set. Based on a supervised scoring method, the records of the data set are processed to indicate their measure of “goodness”. There are various ways by which the records can be processed to indicate a bias during unsupervised clustering processing.