This research empirically investigates the performance of conventional rule interestingness measures and discusses their availability to supporting KDD through system-human interaction in medical domain. We compared the evaluation results by a medical expert and that by selected measures for the rules discovered from a dataset on hepatitis. Recall and 2 Measure 1 demon-strated the highest performance, and all measures showed different trends under our experimental conditions. These results indicated that some measures can predict really interesting rules at a certain level and that their combinational use in system-human interaction will be useful.
|ジャーナル||Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)|
|出版物ステータス||Published - 2004|
|イベント||17th International Conference on Industrial and Engineering Applications of Artificial Intelligence and Expert Systems, IEA/AIE 2004 - Ottowa, Ont., Canada|
継続期間: 2004 5 17 → 2004 5 20
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)