Article ID: | iaor19912034 |
Country: | United Kingdom |
Volume: | 42 |
Start Page Number: | 227 |
End Page Number: | 234 |
Publication Date: | Mar 1991 |
Journal: | Journal of the Operational Research Society |
Authors: | Sorensen S.W., Callahan J.D. |
Keywords: | decision |
An expert system was desired for a group decision-making process. A highly variable data set from previous groups’ decisions was available to simulate past group decisions. This data set has much missing information and contains many possible errors. Classification and regression trees (CART) was selected for rule induction, and compared with multiple linear regression and discriminant analysis. The authors conclude the CART’s decision rules can be used for rule induction. CART uses all available information and can predict observations with missing data. Errors in results from CART compare well with those from multiple linear regression and discriminant analysis. CART results are easier to understand.