Measuring expected effects of interventions based on decision rules
Salvatore Greco, Benedetto Matarazzo, Nello Pappalardo, Roman Słowiński · Journal of Experimental & Theoretical Artificial Intelligence · 2005
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.