计算机科学 ›› 2013, Vol. 40 ›› Issue (Z11): 140-142.
阮晓宏,黄小猛,袁鼎荣,段巧灵
RUAN Xiao-hong,HUANG Xiao-meng,YUAN Ding-rong and DUAN Qiao-ling
摘要: 代价敏感学习方法常常假设不同类型的代价能够被转换成统一单位的同种代价,显然构建适当的代价敏感属性选择因子是个挑战。设计了一种新的异构代价敏感决策树分类器算法,该算法充分考虑了不同代价在分裂属性选择中的作用,构建了一种基于异构代价的分裂属性选择模型,设计了基于代价敏感的剪枝标准。实验结果表明,该方法处理代价机制和属性信息的异质性比现有方法更有效。
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