Comparison between objective interestingness measures and real human interest in medical data mining

Miho Ohsaki; Yoshinori Sato; Shinya Kitaguchi; Hideto Yokoi; Takahira Yamaguchi

doi:10.1007/978-3-540-24677-0_110

Comparison between objective interestingness measures and real human interest in medical data mining

Miho Ohsaki
, Yoshinori Sato
, Shinya Kitaguchi
, Hideto Yokoi
, Takahira Yamaguchi

研究成果: Conference article › 査読

12 被引用数 (Scopus)

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	https://doi.org/10.1007/978-3-540-24677-0_110
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月 17 → 2004 5月 20

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この成果は、次の持続可能な開発目標に貢献しています

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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一般

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10.1007/978-3-540-24677-0_110

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AU - Yamaguchi, Takahira

PY - 2004

Y1 - 2004

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AB - 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.

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JO - Lecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)

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Y2 - 17 May 2004 through 20 May 2004

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Comparison between objective interestingness measures and real human interest in medical data mining

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