Modeling of algorithms of inductive concept formation in "noisy" databases

Authors:
V. N. Vagin;M. V. Fomina;S. G. Antipov
Affiliations:
Department of Applied Mathematics, Moscow Power Engineering Institute, Moscow, Russia;Department of Applied Mathematics, Moscow Power Engineering Institute, Moscow, Russia;Department of Applied Mathematics, Moscow Power Engineering Institute, Moscow, Russia
Venue:
Automatic Documentation and Mathematical Linguistics
Year:
2013

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Abstract

The problem is inductive concept formation in the case of the processing of incomplete, inaccurate, and inconsistent information stored in real data sets. In order to generalize information from real databases it is proposed to use production models and decision trees. Models of noise are presented and the effect of noise on the operation of the proposed generalization algorithms is examined. The results of the program modeling are given.