A modular method for estimating null values in relational database systems

Sj Lee*, Xiaojun Zeng

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Scopus citations

Abstract

There are many methods trying to do the relational database estimation with a highly estimated accuracy rate by constructing a great diversity of methods. This paper presents a modular method for estimating null values in relational database systems, and which is based on a simple fuzzy learning algorithm. However, there exists a conflict between the degree of the interpretability and the accuracy of the approximation in a general fuzzy system. Thus, how to make the best compromise between the accuracy of the approximation and the degree of the interpretability in the entire system is a significant study of the subject. Due to achieve the best compromise, the proposed method does not only integrate advantages of fuzzy system and simple linear regression model, but also introduce a new criterion, differential rate, to enhance the estimated accuracy of the approximation with a highly accuracy of this achievement.

Original languageEnglish
Title of host publicationProceedings - 8th International Conference on Intelligent Systems Design and Applications, ISDA 2008
Pages415-419
Number of pages5
DOIs
StatePublished - 1 Dec 2008
Event8th International Conference on Intelligent Systems Design and Applications, ISDA 2008 - Kaohsiung, Taiwan
Duration: 26 Nov 200828 Nov 2008

Publication series

NameProceedings - 8th International Conference on Intelligent Systems Design and Applications, ISDA 2008
Volume2

Conference

Conference8th International Conference on Intelligent Systems Design and Applications, ISDA 2008
CountryTaiwan
CityKaohsiung
Period26/11/0828/11/08

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