Use of the FRiS-function for taxonomy, attribute selection and decision rule construction

Authors:
Irina A. Borisova;Vladimir V. Dyubanov;Olga A. Kutnenko;Nikolay G. Zagoruiko
Affiliations:
Institute of Mathematics, Russian Academy of Sciences, Novosibirsk, Russia;Institute of Mathematics, Russian Academy of Sciences, Novosibirsk, Russia;Institute of Mathematics, Russian Academy of Sciences, Novosibirsk, Russia;Institute of Mathematics, Russian Academy of Sciences, Novosibirsk, Russia
Venue:
KONT'07/KPP'07 Proceedings of the First international conference on Knowledge processing and data analysis
Year:
2007

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Abstract

The task of simultaneous taxonomy (task S), decision rule construction (task D) and most informative attributes selection (task X) is the combined-type task SDX. We offer a way to solve this type of task with a function of rival similarity (FRiS-function). As a result the set of analyzed objects is divided into K classes (clusters) in the selected subspace of informative attributes according to principles of natural classification. Every cluster is described by a necessary and sufficient set of typical representatives (stolps), which provide maximal similarity of all objects of the training dataset with the nearest stolps. In this paper advantages of the criterion based on the FRiS-function for solving SDX task and other combined-type problems in data mining are shown.