Nabwey, H., Abady, A., Habik, S., Rady, E., Farag, T. (2008). ,N APPROACH TO RULE DISCOVERY IN INCOMPLETE INFORMATION SYSTEMS. test, 31(2), 227-234. doi: 10.21608/erjm.2008.69538
Hossam A. Nabwey; A. N. Abady; S. E Habik; E. A. Rady; T. M Farag. ",N APPROACH TO RULE DISCOVERY IN INCOMPLETE INFORMATION SYSTEMS". test, 31, 2, 2008, 227-234. doi: 10.21608/erjm.2008.69538
Nabwey, H., Abady, A., Habik, S., Rady, E., Farag, T. (2008). ',N APPROACH TO RULE DISCOVERY IN INCOMPLETE INFORMATION SYSTEMS', test, 31(2), pp. 227-234. doi: 10.21608/erjm.2008.69538
Nabwey, H., Abady, A., Habik, S., Rady, E., Farag, T. ,N APPROACH TO RULE DISCOVERY IN INCOMPLETE INFORMATION SYSTEMS. test, 2008; 31(2): 227-234. doi: 10.21608/erjm.2008.69538

,N APPROACH TO RULE DISCOVERY IN INCOMPLETE INFORMATION SYSTEMS

ERJ. Engineering Research Journal
Article 12, Volume 31, Issue 2, April 2008, Pages 227-234    PDF (794.9 K)
Document Type: Original Article
DOI: 10.21608/erjm.2008.69538
Authors
Hossam A. Nabwey1; A. N. Abady1; S. E Habik2; E. A. Rady3; T. M Farag2
1Department of Engineering Mathmatics & Basic Science, Faculty of Engineering, Minoufiya University, Shebin El-Kom, Egypt
2-
3Institute of Statistical Studies &Research (ZSSR), Cairo University, Egypt.
Abstract
This paper introduces a probabilistic rough set approach to rule discovery fiom incomplete
decision tables. The core of the approach is a soft hybrid induction system called the Generalized
Distribution Table and Rough Set System (GDT-RS) for discovering classification rules. The
system is based on a combination of Generalized Distribution Table (GDT) and the Rough Set
methodologies. With every decision rule two conditional probabilities associated, namely the
certainty factor and the coverage factor. The probabilistic properties of the Decision rules are
discussed
Keywords
Rough set theory; incomplete data; Missing attribute values; Generalized Distribution Table (GDT); Rule discovery
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