Incremental Tree-Based Missing Data Imputation with Lexicographic Ordering

被引:0
|
作者
Claudio Conversano
Roberta Siciliano
机构
[1] University of Cagliari,Department of Economics
[2] University of Naples Federico II,Department of Mathematics and Statistics
来源
Journal of Classification | 2009年 / 26卷
关键词
Missing data; Classification and regression tree; FAST splitting algorithm; Lexicographic order; Nonparametric imputation; Data editing;
D O I
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中图分类号
学科分类号
摘要
In the framework of incomplete data analysis, this paper provides a nonparametric approach to missing data imputation based on Information Retrieval. In particular, an incremental procedure based on the iterative use of tree-based method is proposed and a suitable Incremental Imputation Algorithm is introduced. The key idea is to define a lexicographic ordering of cases and variables so that conditional mean imputation via binary trees can be performed incrementally. A simulation study and real data applications are carried out to describe the advantages and the performance with respect to standard approaches.
引用
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页码:361 / 379
页数:18
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