Analysis of the Effectiveness of Machine Learning in Determining Decision Rules for Executive Compensation Planning

Robert H. Michaelsen and Kathleen M. Swigger

Intelligent Systems in Accounting, Finance and Management, 1994, vol. 3, issue 4, 263-278

Abstract: This paper describes the use of a machine‐learning technique to derive executive compensation planning rules. The specific learning technique was AQ15, which constructs rules by classifying sample data according to features or characteristics. The validity of the resulting rules was tested by obtaining a measure of performance called an estimate of the error rate. The machine‐derived rules were then compared to rules made by human experts and by two other versions of AQ15. Although not statistically significant, the machine‐learning version of AQ15 using hypotheses from human experts outperformed the other methods of rule construction.

Date: 1994
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https://doi.org/10.1002/j.1099-1174.1994.tb00070.x

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