caa a22 4500 606217282 CHVBK 20210128101107.0 cr unu---uuuuu 210128e20151001xx s 000 0 eng 10.1007/s10598-015-9293-y doi (NATIONALLICENCE)springer-10.1007/s10598-015-9293-y Kolmakov E. Faculty of Computational Mathematics and Cybernetics, Moscow State University, Moscow, Russia aut Metric Generalization of Classification Algorithms Based on Formal Concept Analysis [Elektronische Daten] [E. Kolmakov] Classification algorithms based on formal concept analysis (FCA) differ in how they process nonbinary descriptions of objects: using them directly as given or after transforming them to binary attributes by a scaling procedure. A common weakness of classifiers of the second type is that they forget the metric structure of the initial attribute space. The main idea of this article is how to utilize the original metric information alongside with order-theoretical relations between objects and attributes. The metric approach substantially reduces the number of classification failures and provides additional information about the objects, thus opening new options for classifier construction. A classifier model is proposed that generalizes some of the existing FCA-based classification algorithm and opens new possibilities for their modification. The article also considers an alternative metric-based approach: specifically, introduction of a distance measure between formal concepts and its use for classifier modification. Springer Science+Business Media New York, 2015 formal concept analysis nationallicence classification problem nationallicence machine learning nationallicence metric methods nationallicence pseudometric nationallicence Computational Mathematics and Modeling Springer US; http://www.springer-ny.com 26/4(2015-10-01), 566-576 1046-283X 26:4<566 2015 26 10598 https://doi.org/10.1007/s10598-015-9293-y text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s10598-015-9293-y text/html Onlinezugriff via DOI NATIONALLICENCE 100 1- Kolmakov E. Faculty of Computational Mathematics and Cybernetics, Moscow State University, Moscow, Russia aut NATIONALLICENCE 773 0- Computational Mathematics and Modeling Springer US; http://www.springer-ny.com 26/4(2015-10-01), 566-576 1046-283X 26:4<566 2015 26 10598