Techniques for dealing with missing values in classification

被引：0
|
作者：
Liu, WZ
White, AP
Thompson, SG
Bramer, MA
机构：
[1] Univ Portsmouth, Artificial Intelligence Res Grp, Dept Informat Sci, Milton PO4 8JF, Hampshire, England
[2] Univ Birmingham, Sch Math & Stat, Birmingham B15 2TT, W Midlands, England
来源：
ADVANCES IN INTELLIGENT DATA ANALYSIS: REASONING ABOUT DATA | 1997年 / 1280卷
关键词：
missing values; dynamic path generation; intelligent data analysis; inductive learning; knowledge discovery; data mining; machine learning;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
A brief overview of the history of the development of decision tree induction algorithms is followed by a review of techniques for dealing with missing attribute values in the operation of these methods. The technique of dynamic path generation is described in the context of tree-based classification methods. The waste of data which can result from casewise deletion of missing values in statistical algorithms is discussed and alternatives proposed.
引用
收藏
页码：527 / 536
页数：10
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