Measuring expected effects of interventions based on decision rules

Salvatore Greco, B. Matarazzo, N. Pappalardo, R. Slowinski

Research output: Contribution to journalArticlepeer-review

Abstract

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.
Original languageEnglish
Pages (from-to)103-118
Number of pages16
JournalJournal of Experimental & Theoretical Artificial Intelligence
Volume17
Issue number1-2
DOIs
Publication statusPublished - 2005

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