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A Rough Set Approach to Incomplete Data

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Rough Sets and Knowledge Technology (RSKT 2015)

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Abstract

This paper presents main directions of research on a rough set approach to incomplete data. First, three different types of lower and upper approximations, based on the characteristic relation, are defined. Then an idea of the probabilistic approximation, an extension of lower and upper approximations, is presented. Local probabilistic approximations are also discussed. Finally, some special topics such as consistency of incomplete data and a problem of increasing data set incompleteness to improve rule set quality, in terms of an error rate, are discussed.

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Authors and Affiliations

  1. Department of Electrical Engineering and Computer Science, University of Kansas, Lawrence, KS, 66045, USA

    Jerzy W. Grzymala-Busse

  2. Department of Expert Systems and Artificial Intelligence, University of Information Technology and Management, 35-225, Rzeszow, Poland

    Jerzy W. Grzymala-Busse

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  1. Jerzy W. Grzymala-Busse
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Correspondence to Jerzy W. Grzymala-Busse .

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Editors and Affiliations

  1. University of Milano-Bicocca, Milano, Italy

    Davide Ciucci

  2. Chongqing University of Posts and Telecommunications, Chongqing, China

    Guoyin Wang

  3. Indian Statistical Institute, Kolkata, India

    Sushmita Mitra

  4. Zhejiang Ocean University, Zhejiang, China

    Wei-Zhi Wu

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Grzymala-Busse, J.W. (2015). A Rough Set Approach to Incomplete Data. In: Ciucci, D., Wang, G., Mitra, S., Wu, WZ. (eds) Rough Sets and Knowledge Technology. RSKT 2015. Lecture Notes in Computer Science(), vol 9436. Springer, Cham. https://doi.org/10.1007/978-3-319-25754-9_1

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