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Authors: Patrick G. Clark 1 and Jerzy Grzymala-Busse 2

Affiliations: 1 University of Kansas, United States ; 2 University of Kansas and Polish Academy of Sciences, United States

Keyword(s): Consistency, Incomplete Data, Missing Attribute Values, Rough Set Theory.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Biomedical Engineering ; Business Analytics ; Data Analytics ; Data Engineering ; Data Mining ; Databases and Information Systems Integration ; Datamining ; Enterprise Information Systems ; Health Information Systems ; Knowledge Discovery and Information Retrieval ; Knowledge-Based Systems ; Sensor Networks ; Signal Processing ; Soft Computing ; Symbolic Systems

Abstract: In this paper we introduce an idea of consistency for incomplete data sets. Consistency is well-known for completely specified data sets, where a data set is consistent if for any two cases with equal all attribute values, both cases belong to the same concept. We generalize the definition of consistency for incomplete data sets using rough set theory. For incomplete data sets there exist three definitions of consistency. We discuss two types of missing attribute values: lost values and ``do not care'' conditions. We illustrate an idea of consistency for incomplete data sets using experiments on many data sets with missing attribute values derived from five benchmark data sets. Results of our paper may be applied for increasing the efficiency of mining incomplete data.

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Paper citation in several formats:
Clark, P. G. and Grzymala-Busse, J. (2013). Consistency of Incomplete Data. In Proceedings of the 2nd International Conference on Data Technologies and Applications - DATA; ISBN 978-989-8565-67-9; ISSN 2184-285X, SciTePress, pages 80-87. DOI: 10.5220/0004490300800087

@conference{data13,
author={Patrick G. Clark and Jerzy Grzymala{-}Busse},
title={Consistency of Incomplete Data},
booktitle={Proceedings of the 2nd International Conference on Data Technologies and Applications - DATA},
year={2013},
pages={80-87},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004490300800087},
isbn={978-989-8565-67-9},
issn={2184-285X},
}

TY - CONF

JO - Proceedings of the 2nd International Conference on Data Technologies and Applications - DATA
TI - Consistency of Incomplete Data
SN - 978-989-8565-67-9
IS - 2184-285X
AU - Clark, P.
AU - Grzymala-Busse, J.
PY - 2013
SP - 80
EP - 87
DO - 10.5220/0004490300800087
PB - SciTePress

- Science and Technology Publications, Lda.
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