Decision tree induction with a constrained number of leaf nodes
學年 104
學期 2
出版(發表)日期 2016-04-15
作品名稱 Decision tree induction with a constrained number of leaf nodes
著者 Chia-Chi Wu; Yen-Liang Chen; Yi-Hung Liu; Xiang-Yu Yang
著錄名稱、卷期、頁數 Applied Intelligence 45(3), p.673-685
摘要 With the advantages of being easy to understand and efficient to compute, the decision tree method has long been one of the most popular classifiers. Decision trees constructed with existing approaches, however, tend to be huge and complex, and consequently are difficult to use in practical applications. In this study, we deal with the problem of tree complexity by allowing users to specify the number of leaf nodes, and then construct a decision tree that allows maximum classification accuracy with the given number of leaf nodes. A new algorithm, the Size Constrained Decision Tree (SCDT), is proposed with which to construct a decision tree, paying close attention on how to efficiently use the limited number of leaf nodes. Experimental results show that the SCDT method can successfully generate a simpler decision tree and offers better accuracy.
關鍵字 Classification;Data mining;Decision tree;Constraint tree
語言 en
ISSN 1573-7497
期刊性質 國外
收錄於 SCI
國別 USA
出版型式 ,電子版,紙本

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