An Extended Version of the CPT-based Estimation for Missing Values in Nominal Attributes

An Extended Version of the CPT-based Estimation for Missing Values in Nominal Attributes

초록

The causal network represents the knowledge related to the dependency relationship between all attributes. If the causal network is available, the dependency relationship can be employed to estimate the missing values for improving the estimation performance. However, the previous method had a limitation in that it did not consider the bidirectional characteristic of the causal network. The proposed method considers the bidirectional characteristic by applying prior and posterior conditions, so that it outperforms the previous method.

키워드

Causal Network; Missing Values; Dependency Relationship; Estimation
제목
An Extended Version of the CPT-based Estimation for Missing Values in Nominal Attributes
제목 (타언어)
An Extended Version of the CPT-based Estimation for Missing Values in Nominal Attributes
저자
고송; 김대원
발행일
2010-12
저널명
International Journal of Fuzzy Logic and Intelligent Systems
권
10
호
4
페이지
253 ~ 258