NDLI: Attribute reduction based on the grey relational analysis and dynamic programming

Content Provider	IEEE Xplore Digital Library
Author	Yang Yang Xiuqin Wang
Copyright Year	2013
Description	Author affiliation: Inf. Sci. & Technol. Sch., Bohai Univ., Jinzhou, China (Xiuqin Wang) \|\| Sch. of Eng., Bohai Univ., Jinzhou, China (Yang Yang)
Abstract	Attribute reduction is an important method in improving the efficiency and the quality of data mining, especially for high dimension data. Therefore, the reduction of data dimensions shall be achieved with higher efficiency. There are many multi-feature attributes in the real project. Many existing works are devoted into finding optimal reducts. In these kinds of methods, the feature attribute importance is always needed in order to do attribute reduction. A grey system has a level of information between black and white. Grey relational analysis (GRA) is a multi-attribute decision making (MADM) method that can be used to find the relationships between one major sequence and the other sequences. In this paper, a method combined grey relational analysis (GRA) with dynamic programming is presented. Considering both the relationship between individual feature attributes with the target attribute and the relationship between different feature attribute, the relational data in our paper include two parts: one is the grey relational grade between ith and jth attribute, the other is jth attribute's contribution to the aim data. Dynamic programming is proposed to reduce attributes of low interest, which can be used to find the best feature in the residue feature attributes with the relational data. Based on the longest length in the dynamic programming, we can easily get the importance of attribute sorting and do attribute reduction. The measure of the attribute importance will be more rational. The proposed method will play an important role in the attribute reduction, data mining, decision analysis and so on. Quality data will be supply for the further processing subsequently.
Sponsorship	IEEE Circuits Syst. Soc.
Starting Page	697
Ending Page	701
File Size	221125
Page Count	5
File Format	PDF
ISBN	9781467347143
ISSN	21579563
DOI	10.1109/ICNC.2013.6818065
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-07-23
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Computer science Correlation grey relational analysis (GRA) dynamic programming Educational institutions grey system attribute reduction Dynamic programming Data mining Sorting Principal component analysis
Content Type	Text
Resource Type	Article

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