In this technical report , two new algorithms based upon frequent patterns are proposed. One algorithm is a classification method. The other one is an algorithm for target group selection. In both algorithms, first of all, the collection of frequent patterns in the training set is constructed. Choosing an appropriate data structure allows us to keep the full collection of frequent patterns in memory. The classification method utilizes directly this collection. Target group selection is a known problem in direct marketing. Our selection algorithm is based upon the collection of frequent patterns.

, , ,
, , ,
Erasmus Research Institute of Management
hdl.handle.net/1765/50
ERIM Report Series Research in Management
Erasmus Research Institute of Management

Pijls, W.H.L.M, & Potharst, R. (2000). Classification and Target Group Selection Based Upon Frequent Patterns (No. ERS-2000-40-LIS). ERIM Report Series Research in Management. Erasmus Research Institute of Management. Retrieved from http://hdl.handle.net/1765/50