Mining a Small Medical Data Set by Integrating the Decision Tree and t-test
學年 100
學期 1
出版（發表）日期 2011-12-01
作品名稱 Mining a Small Medical Data Set by Integrating the Decision Tree and t-test
作品名稱（其他語言）
著者 Chang, Ming-Yang; Shih, Chien-Chou; Chiang, Ding-An; Chen, Chun-Chi
單位 淡江大學資訊傳播學系; 淡江大學資訊工程學系
出版者 Oulu: Academy Publisher
著錄名稱、卷期、頁數 Journal of Software 6(12), pp.2515-2520
摘要 Although several researchers have used statistical methods to prove that aspiration followed by the injection of 95% ethanol left in situ (retention) is an effective treatment for ovarian endometriomas, very few discuss the different conditions that could generate different recovery rates for the patients. Therefore, this study adopts the statistical method and decision tree techniques together to analyze the postoperative status of ovarian endometriosis patients under different conditions. Since our collected data set is small, containing only 212 records, we use all of these data as the training data. Therefore, instead of using a resultant tree to generate rules directly, we use the value of each node as a cut point to generate all possible rules from the tree first. Then, using t-test, we verify the rules to discover some useful description rules after all possible rules from the tree have been generated. Experimental results show that our approach can find some new interesting knowledge about recurrent ovarian endometriomas under different conditions.
關鍵字 Data mining; Decision tree; t-test; p-value; Ovarian endometriomas
語言 en
ISSN 1796-217X
期刊性質 國外
收錄於 EI
產學合作
通訊作者
審稿制度 是
國別 FIN
公開徵稿
出版型式 紙本
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