title: ILLM--inductive learning algorithm as a method for prediction of life expectancy achieving.
abstract: The aim of the paper was to use inductive learning algorithm ILLM in the field of epidemiology, for prediction the life expectancy achieving. Data base comprised results of epidemiological investigation in some regions of Croatia. Overall accuracies for different samples and corresponding rules produced by ILLM algorithm, showed some interesting results. Algorithm can be seen as having the capacity to forecast 'achieving the life expectancy'. In the same time algorithm was not able to make a good forecast for 'not achieving the life expectancy'.
authors.affiliation: University of Zagreb, Medical School, Andrija Stampar School of Public Health, Croatia. jkern@andrija.snz.hr
authors.forename: J
authors.initials: J
authors.lastname: Kern
authors.forename: D
authors.initials: D
authors.lastname: Gamberger
authors.forename: Z
authors.initials: Z
authors.lastname: Sonicki
authors.forename: S
authors.initials: S
authors.lastname: Vuletić
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D017523:Croatia; D005260:Female; D006305:Health Status Indicators; D006801:Humans; D008017:Life Expectancy; D008297:Male; D008432:Mathematical Computing; D008875:Middle Aged; D012984:Software