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A technique for retrieving cause-and-effect relationships from optimized fact bases

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Abstract

A technique for retrieving causal connections of binary relationships from a set of fact bases is suggested. The fact bases are formed for the target properties of each class of objects. The class descriptions are formed by habituation on data from a loosely formalized object domain. The habituation is organized using a co-evolutional genetic algorithm that reduces the initial feature space. The cause-and-effect relationships for all target properties are sought by the formed optimized class descriptions using stage one of the JSM method. The suggested technique is suitable for the analysis of the full data in small amounts and large incomplete data arrays. Several model experiments using the MIMIC II medical database were conducted.

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Authors and Affiliations

  1. Institute for Systems Analysis, Russian Academy of Sciences, Moscow, 117312, Russia

    A. I. Panov & A. V. Shvets

  2. Moscow State Technological Institute STANKIN, Moscow, 127994, Russia

    G. D. Volkova

Authors
  1. A. I. Panov
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  2. A. V. Shvets
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  3. G. D. Volkova
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Correspondence to A. I. Panov.

Additional information

Original Russian Text © A.I. Panov, A.V. Shvets, G.D. Volkova, 2015, published in Iskusstvennyi Intellekt i Prinyatie Reshenii, 2015, No. 1, pp. 27–34.

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Panov, A.I., Shvets, A.V. & Volkova, G.D. A technique for retrieving cause-and-effect relationships from optimized fact bases. Sci. Tech.Inf. Proc. 42, 420–425 (2015). https://doi.org/10.3103/S0147688215060039

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  • DOI: https://doi.org/10.3103/S0147688215060039

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