,N APPROACH TO RULE DISCOVERY IN INCOMPLETE INFORMATION SYSTEMS | ||||
| ERJ. Engineering Research Journal | ||||
| Article 12, Volume 31, Issue 2, April 2008, Page 227-234 PDF (794.9 K) | ||||
| Document Type: Original Article | ||||
| DOI: 10.21608/erjm.2008.69538 | ||||
 View on SCiNiTO | ||||
| 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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