Keywords
audit selection rules, genetic algorithms, auditing, data approach
Abstract
The construction of expert systems typically require the availability of expertise that can be modeled. However, there are many important problems where no expertise exists, yet there is a wealth of data indicating results in different situations. Machine learning algorithms attempt to discover rules which capture the regularities that exists in such data.
BYU ScholarsArchive Citation
Greene, David P.; Meservy, Rayman D.; and Smith, Stephen F., "Learn Audit Selection Rules From Data: A Genetic Algorithms Approach" (1992). Faculty Publications. 3236.
https://scholarsarchive.byu.edu/facpub/3236
Document Type
Peer-Reviewed Article
Publication Date
1992
Permanent URL
http://hdl.lib.byu.edu/1877/6047
Language
English
College
Marriott School of Management
Department
Accountancy