Abstract
The identification of workplaces (establishments) most likely to pay low wages is an essential component of effectively monitoring a minimum wage. The main method utilised in this paper is the Variable Precision Rough Sets (VPRS) model, which constructs a set of decision ‘if... then...’ rules. These rules are easily readable by non-specialists and predict the proportion of low paid employees in an establishment. Through a ‘leave n out’ approach a standard error on the predictive accuracy of the sets of rules is calculated, also the importance of the descriptive characteristics is exposited based on their use. To gauge the effectiveness of the VPRS analysis, comparisons are made to a series of decision tree analyses.
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© 2002 Springer-Verlag Berlin Heidelberg
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Beynon, M.J. (2002). The Identification of Low-Paying Workplaces: An Analysis Using the Variable Precision Rough Sets Model. In: Alpigini, J.J., Peters, J.F., Skowron, A., Zhong, N. (eds) Rough Sets and Current Trends in Computing. RSCTC 2002. Lecture Notes in Computer Science(), vol 2475. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45813-1_70
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DOI: https://doi.org/10.1007/3-540-45813-1_70
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