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 from the rest by aggregating the latter into a pseudo-class; alternatively, classes are treated separately without coordinating their profiles with those of the other classes. We introduce the concise all pairs profiling (CAPP) method for concise, intelligible, and approximate profiling of large classifications. The method compares all classes pairwise and then minimizes the 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 science are demonstrated.

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