Establish a discern model of under skewed class distribution

Cien Yun Dai, Chi Jun Lu, Chiu Huin Liao, Chen Chieh Yeh

研究成果: 書貢獻/報告類型會議貢獻

摘要

Under Skewed Class Distribution Data (SCDD) Real-world applications often involve highly skewed data in decision outcomes. Such a highly skewed class distribution problem, if not properly addressed, would imperil the resulting learning effectiveness. We use one hospital Central Venous Catheter Insertion data for the training data. Among them find CVP-tip attribute are skewed class distribution. The paper uses under-sampling over-sampling and cost-sensitivity to solve SCDD problem. And then use C4.5 algorithms to build up classification model for the central venous catheter insertion. Verify via the expert that use this model can effectively help the medical expert to extract out it about Central Venous Catheter Insertion good knowledge rules.

原文英語
主出版物標題IMECS 2007 - International MultiConference of Engineers and Computer Scientists 2007
頁面801-804
頁數4
出版狀態已發佈 - 2007 十二月 1
事件International MultiConference of Engineers and Computer Scientists 2007, IMECS 2007 - Kowloon, 香港
持續時間: 2007 三月 212007 三月 23

出版系列

名字Lecture Notes in Engineering and Computer Science
ISSN(列印)2078-0958

其他

其他International MultiConference of Engineers and Computer Scientists 2007, IMECS 2007
國家香港
城市Kowloon
期間2007/03/212007/03/23

ASJC Scopus subject areas

  • Computer Science (miscellaneous)

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