抄録
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.
| 本文言語 | English |
|---|---|
| ページ（範囲） | 1072-1081 |
| ページ数 | 10 |
| ジャーナル | Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science) |
| 巻 | 3029 |
| DOI | |
| 出版ステータス | Published - 2004 |
| 外部発表 | はい |
| 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
- 理論的コンピュータサイエンス
- コンピュータ サイエンス（全般）
UN SDG
この成果は、次の持続可能な開発目標に貢献しています
