Probabilistic generalization of formal concepts

An inductive probabilistic approach to formal concept analysis (FCA) is proposed in which probability on formal contexts is considered; probabilistic formal concepts that have predictive force are defined: nonclassified objects can be assigned to earlier found probabilistic formal concepts; random a...

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Published in:Programming and computer software 2012-09, Vol.38 (5), p.219-230
Main Authors: Vityaev, E. E., Demin, A. V., Ponomaryov, D. K.
Format: Article
Language:English
Subjects:
Artificial Intelligence
Computer Science
Operating Systems
Random noise
Software Engineering
Software Engineering/Programming and Operating Systems
Statistical analysis
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description An inductive probabilistic approach to formal concept analysis (FCA) is proposed in which probability on formal contexts is considered; probabilistic formal concepts that have predictive force are defined: nonclassified objects can be assigned to earlier found probabilistic formal concepts; random attributes are eliminated from probabilistic formal concepts; probabilistic formal concepts are robust with respect to data noise. A result of experiment is presented in which formal concepts (in their standard definition in FCA) are first distorted by random noise and then recovered by detecting probabilistic formal concepts.
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subjects Artificial Intelligence
Computer Science
Operating Systems
Random noise
Software Engineering
Software Engineering/Programming and Operating Systems
Statistical analysis
title Probabilistic generalization of formal concepts
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