Variable precision rough set model
Journal of Computer and System Sciences
FUSINTER: a method for discretization of continuous attributes
International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems
Machine Learning
An Investigation of beta-Reduct Selection within the Variable Precision Rough Sets Model
RSCTC '00 Revised Papers from the Second International Conference on Rough Sets and Current Trends in Computing
An Extended Chi2 Algorithm for Discretization of Real Value Attributes
IEEE Transactions on Knowledge and Data Engineering
Determination of the threshold value β of variable precision rough set by fuzzy algorithms
International Journal of Approximate Reasoning
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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.