The following publications are possibly variants of this publication:
- Experiments on Data with Three Interpretations of Missing Attribute Values - A Rough Set ApproachJerzy W. Grzymala-Busse, Steven Santoso. iis 2006: 143-152 [doi]
- An Experimental Comparison of Three Rough Set Approaches to Missing Attribute ValuesJerzy W. Grzymala-Busse, Witold J. Grzymala-Busse. trs, 6:31-50, 2007. [doi]
- A Rough Set Approach to Data with Missing Attribute ValuesJerzy W. Grzymala-Busse. rskt 2006: 58-67 [doi]
- Mining data with numerical attributes and missing attribute values - A rough set approachJerzy W. Grzymala-Busse, Zdzislaw S. Hippe. grc 2011: 214-219 [doi]
- Rough Set Strategies to Data with Missing Attribute ValuesJerzy W. Grzymala-Busse. In Tsau Young Lin, Setsuo Ohsuga, Churn-Jung Liau, Xiaohua Hu, editors, Foundations and Novel Approaches in Data Mining. Volume 9 of Studies in Computational Intelligence, pages 197-212, Springer, 2006. [doi]
- A Comparison of Some Rough Set Approaches to Mining Symbolic Data with Missing Attribute ValuesJerzy W. Grzymala-Busse. ismis 2011: 52-61 [doi]
- Coping with Missing Attribute Values Based on Closest Fit in Preterm Birth Data: A Rough Set ApproachJerzy W. Grzymala-Busse, Witold J. Grzymala-Busse, Linda K. Goodwin. ci, 17(3):425-434, 2001.