SPSS Clementine决策树建模在图书馆中的应用
of reader borrowing frequency is built with C5.0 in mining tool of SPSS Clementine. The decision tree classifies readers into three groups： activing readers， common readers and silent readers. The mined data come from reader borrowing records of the library of university of international relations. The results show readers' identity， major， grade and gender have an important effect on borrowing amount. The borrowing demand of junior students is great， while that of senior students is small. The library readers may be classified by refering to decision tree classification to provide theoretical evident for adjusting borrowing authority.Key words： decision tree； classification； library； Clementine； borrowing authority0 引言数据挖掘能从大量数据中发现有用的知识，目前己成功应用于各个领域。图书馆系统积累了大量读者数据，研究如何将数据挖掘有效地用于图书馆[1-4]，变数据为知识，从而更好地为读者服务，是数据挖掘和图书馆工作者的共同责任。决策树分类是数据挖掘中的一种重要方法，该方法通过对已有数据的学习，识别影响对象分类的若干因素
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