audit selection rules, genetic algorithms, auditing, data approach
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.
Marriott School of Management