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Measuring expected effects of interventions based on decision rules

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Decision rules induced from a data set represent knowledge patterns relating premises and decisions in ' if … , then …' statements. Premise is a conjunction of elementary conditions relative to independent variables and decision is a conclusion relative to dependent variables. Given a set of decision rules induced from a data set, it is useful to estimate possible effects on the dependent variables caused by an intervention on some independent variables. The authors introduce a methodology for quantifying the impact of a strategy of intervention based on a decision rule induced from data. While the usual interestingness measures of decision rules are taking into account only characteristics of universe U where they come from, the measures of efficiency of intervention depend also on characteristics of universe U ′ where intervention takes place. The authors are considering the intervention on a single independent variable and on a combination of these variables.
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Keywords: Decision rules; Efficiency measure; Expected effects; Intervention; Knowledge discovery

Document Type: Research Article

Affiliations: Institute of Computing Science, Poznan University of Technology 60-965 Poznan, and Institute for Systems Research Polish Academy of Sciences 01-447 Warsaw Poland

Publication date: January 1, 2005

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