Suitable Domains for Using Ordered Attribute Trees to Impute Missing Values

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概要

• 論文の詳細を見る

• Using decision trees to fill the missing values in data has been shown experimentally to be useful in some domains. However, this is not the general case. In other domains, using decision trees for imputing missing attribute values does not outperform other methods. Trying to identify the reasons behind the success or failure of the various methods for filling missing values on different domains can be useful for deciding the technique to be used when learning concepts from a new domain with missing values. This paper presents a technique by which to approach to previous goal and presents the results of applying the technique on predicting the success or failure of a method that uses decision trees to fill the missing values in an ordered manner. Results are encouraging because the obtained decision tree is simple and it can even provide hints for further improvement on the use of decision trees to impute missing attribute values.

• 社団法人電子情報通信学会の論文
• 2001-02-01

著者

• Numao Masayuki

  Dept. Of Computer Science Graduate School Of Information Sciences And Engineering Tokyo Institute Of

• Lobo Oscar-ortega

  Dept. Of Systems Engineering Faculty Of Engineering University Of Antioquia

関連論文

• Suitable Domains for Using Ordered Attribute Trees to Impute Missing Values
• Ordered Estimation of Missing Values for Propositional Learning

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