An instance-based learning approach based on grey relational structure

Huang, Chi-Chun; Lee, Hahn-Ming

doi:10.1007/s10489-006-0105-0

Cited by 8 publications

(2 citation statements)

References 35 publications

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“…However, which devoid of wholeness, it is only a partnering comparison. The set-point topology is characterized by neighbor goodness, namely the wholeness, but, devoid of numerical measure [3][4][5].Therefore, by cooperating the distance space with point-set topology, the grey relational space is established, which can be crystallize as Distance space+ set-point topology=GR space Differing from the traditional mathematical analysis, GRA provides a simple scheme to analyze the series relationships or the system behavior, even if the give information is few [6][7].…”

Section: Characteristics Of Gray Correlation Analysis and The Compara...mentioning

confidence: 99%

Failure Modes Analysis of Electromagnetic Flowmeter Based on Grey Relational Analysis

Zhou

Qin

et al. 2010

AMM

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Firstly this paper introduces gray relation analysis, and then it draws various reasons of electromagnetic flowmeter malfunction in combination with data provided by one company. And the paper calculates the probabilities of the various reasons adopting classical statistics, and equalizes these failure rate data to get sequence difference, and then obtains grey incidence coefficient and correlation degree. Then the paper sorts these correlation degrees to confirm the influence degree of the failure modes. Finally, the bleaching information required is obtained.

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Section: Characteristics Of Gray Correlation Analysis and The Compara...mentioning

confidence: 99%

Failure Modes Analysis of Electromagnetic Flowmeter Based on Grey Relational Analysis

Zhou

Qin

et al. 2010

AMM

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“…A grey-based pattern classification model (instance-based learning approach) is presented in (Huang and Lee, 2006) to identify new, unseen instances or examples. In this approach, grey relational analysis (GRA) (Deng, 1984;Deng, 1989a;Deng, 1989b) is adopted as a similarity function to precisely represent the connections among all instances or examples in a specific classification problem.…”

Section: Grey-based Pattern Classification Modelmentioning

confidence: 99%

A novel grey‐based feature ranking method for feature subset selection

Huang

Chang

Yang

2008

Journal of the Chinese Institute of Engineers

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A novel grey-based feature ranking method for feature subset selection, Journal of the Chinese Institute of Engineers, 31:3, 509-514, ABSTRACTIn this paper, a novel grey-based feature ranking method for feature subset selection is proposed. The classification effectiveness of each attribute of a specific classification problem is proposed and then each attribute can be ranked. Features with higher classification effectiveness are more important and relevant and thus considered as the final feature subset for pattern classification. Experiments performed on various application domains are reported to demonstrate the performance of the proposed approach. The proposed approach yields better performance than other existing feature subset selection methods and is helpful for improving the classification accuracy in pattern classification.

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A Novel Hybrid Taguchi-Grey-Based Method for Feature Subset Selection

Chang

Sun

Lecture Notes in Computer Science

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In this paper, a novel hybrid Taguchi-Grey-based method for feature subset selection is proposed. The two-level orthogonal array is employed in the proposed method to provide a well-organized and balanced comparison of two levels of each feature (i.e., the feature is selected for pattern classification or not) and interactions among all features in a specific classification problem. That is, this two-dimensional matrix is mainly used to reduce the feature subset evaluation efforts prior to the classification procedure. Accordingly, the greybased nearest neighbor rule and the signal-to-noise ratio (SNR) are used to evaluate and optimize the features of the specific classification problem. In this manner, important and relevant features can be identified for pattern classification. Experiments performed on different application domains are reported to demonstrate the performance of the proposed hybrid Taguchi-Greybased method. It can be easily seen that the proposed method yields superior performance and is helpful for improving the classification accuracy in pattern classification.

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An instance-based learning approach based on grey relational structure

Cited by 8 publications

References 35 publications

Failure Modes Analysis of Electromagnetic Flowmeter Based on Grey Relational Analysis

Failure Modes Analysis of Electromagnetic Flowmeter Based on Grey Relational Analysis

A novel grey‐based feature ranking method for feature subset selection

A Novel Hybrid Taguchi-Grey-Based Method for Feature Subset Selection

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