Probabilistic rule induction from a medical research study database.
This paper describes and applies the ITRULE algorithm, a generalized rule induction algorithm of Smyth and Goodman, for the exploratory analysis of a subset of data from the National Heart, Lung, and Blood Institute Growth and Health Study. The ITRULE algorithm is used as an effective, parsimonious method for detecting informative relationships in a large set of study variables. The potential complexity of the search among many variables is controlled by applying an information theoretic rule preference measure, the J-measure, to limit rule specialization.
Clarke
E J
EJ
Maryland Medical Research Institute, 600 Wyndhurst Ave., Baltimore, Maryland, 21210, USA.
Waclawiw
M A
MA
D000367:Age Factors; D000465:Algorithms; D044383:Black People; D001794:Blood Pressure; D002318:Cardiovascular Diseases / Q000209:etiology; D002648:Child; D002657:Child Development; D002784:Cholesterol / Q000097:blood; D015331:Cohort Studies; D005260:Female; D006801:Humans; D007182:Income; D007256:Information Systems; D009316:National Institutes of Health (U.S.); D016571:Neural Networks, Computer; D009765:Obesity / Q000150:complications; D011336:Probability; D012307:Risk Factors; D014481:United States; D044465:White People; D001741:Black or African American
D002784:Cholesterol