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    政大機構典藏 > 商學院 > 資訊管理學系 > 期刊論文 >  Item 140.119/72893
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/72893

    Title: A Comparative Study of Medical Data Classification Methods Based on Decision Tree and System Reconstruction Analysis
    Authors: 湯宗益
    Tang, Tzung-i;Zheng, Gang;Huang, Yalou;Shu, Guangfu;Wang, Pengtao
    Contributors: 資管系
    Date: 2005-06
    Issue Date: 2015-01-14 16:35:30 (UTC+8)
    Abstract: Abstract. This paper studies medical data classification methods, comparing decision tree and system reconstruction analysis as applied to heart disease medical data mining. The data we study is collected from patients with coronary heart disease. It has 1,723 records of 71 attributes each. We use the system-reconstruction method to weight it. We use decision tree algorithms, such as induction of decision trees (ID3), classification and regression tree (C4.5), classification and regression tree (CART), Chi-square automatic interaction detector (CHAID), and exhausted CHAID. We use the results to compare the correction rate, leaf number, and tree depth of different decision-tree algorithms. According to the experiments, we know that weighted data can improve the correction rate of coronary heart disease data but has little effect on the tree depth and leaf number.
    Data Type: article
    Appears in Collections:[資訊管理學系] 期刊論文

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