Concise, intelligible, and approximate profiling of multiple classes

When a dataset involves multiple classes, there is often a need to express the key contrasting features among these classes in humanly understandable terms, that is, to profile the classes. Commonly, one class is contrasted f rom the rest by aggregating the latter into a pseudo-class; alternatively, classes are treated separately without coordinating their profiles with tho se of the other classes. We introduce the concise all pairs profiling (CAPP ) method for concise, intelligible, and approximate profiling of large clas sifications. The method compares all classes pairwise and then minimizes th e overall number of features needed to guarantee that each pair of classes is contrasted by at least one feature. Then each class profile gets its own minimized list of features, annotated with how these features contrast the class from the others. Significant applications to social and natural scie nce are demonstrated. (C) 2000 Academic Press.