Vladimir Pericliev

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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 pro"le 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(More)
The paper describes a novel computational tool for multiple concept learning. Unlike previous approaches, whose major goal is prediction on unseen instances rather than the legibility of the output, our MPD (Maximally Parsimonious Discrimination) program emphasizes the conciseness and intelligibility of the resultant class descriptions, using three(More)
A discovery system for detecting correspondences in data is described, based on the familiar induction methods of J. S. Mill. Given a set of observations, the system induces the " causally " related facts in these observations. Its application to empirical linguistic discovery is described. The paper is organized as follows. I begin the discussion by(More)