Bell, D.A.; Guan, J.W.: Computational methods for rough classification and discovery (1998)
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- Abstract
- Rough set theory is a mathematical tool to deal with vagueness and uncertainty. To apply the theory, it needs to be associated with efficient and effective computational methods. A relation can be used to represent a decison table for use in decision making. By using this kind of table, rough set theory can be applied successfully to rough classification and knowledge discovery. Presents computational methods for using rough sets to identify classes in datasets, finding dependencies in relations, and discovering rules which are hidden in databases. Illustrates the methods with a running example from a database of car test results
- Footnote
- Contribution to a special issue devoted to knowledge discovery and data mining
- Type
- a
