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The Identification of Low-Paying Workplaces: An Analysis using the Variable Precision Rough Sets Model

Beynon, Malcolm James 2002. The Identification of Low-Paying Workplaces: An Analysis using the Variable Precision Rough Sets Model. Presented at: Third International Conference on Rough Sets and Current Trends in Computing (RSCTC2002), Malvern, PA, USA, 14-16 October 2002. Published in: Alpigini, J. J., Peters, J. F., Skowron, A. and Zhong, N. eds. Rough Sets and Current Trends in Computing: Third International Conference on Rough Sets and Current Trends in Computing, RSCTC2002, Malvern, PA, USA, October 14-16, 2002. Proceedings. Lecture Notes in Computer Science , vol. 2475. Berlin: Springer, pp. 530-537. 10.1007/3-540-45813-1_70

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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.

Item Type: Conference or Workshop Item (Paper)
Date Type: Publication
Status: Published
Schools: Business (Including Economics)
Subjects: H Social Sciences > H Social Sciences (General)
H Social Sciences > HA Statistics
H Social Sciences > HD Industries. Land use. Labor
Q Science > QA Mathematics
Publisher: Springer
ISBN: 9783540442745
Related URLs:
Last Modified: 04 Jun 2017 04:20
URI: http://orca-mwe.cf.ac.uk/id/eprint/37032

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