A Novel Approach for Reducing Attributes and Its Application to Small Enterprise Financing Ability Evaluation
Attribute reduction is viewed as a kind of preprocessing steps for reducing large dimensionality in data mining of all complex systems. A great deal of researchers have proposed various approaches to reduce attributes or select key features in multicriteria decision making evaluation. In practice, t...
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
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Wiley
2018-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2018/1032643 |
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| author | Baofeng Shi Bin Meng Hufeng Yang Jing Wang Wenli Shi |
| author_facet | Baofeng Shi Bin Meng Hufeng Yang Jing Wang Wenli Shi |
| author_sort | Baofeng Shi |
| collection | DOAJ |
| description | Attribute reduction is viewed as a kind of preprocessing steps for reducing large dimensionality in data mining of all complex systems. A great deal of researchers have proposed various approaches to reduce attributes or select key features in multicriteria decision making evaluation. In practice, the existing approaches for attribute reduction focused on improving the classification accuracy or saving the cost of computational time, without considering the influence of the reduction results on the original data set. To help address this gap, we develop an advanced novel attribute reduction approach combining Pearson correlation analysis with F test significance discrimination for the screening and identification of key characteristics related to the original data set. The proposed model has been verified using the financing ability evaluation data of 713 small enterprises of a city commercial bank in China. And the experimental results show that the proposed reduction model is efficient and effective. Moreover, our experimental findings help to locate the qualified partners and alleviate the difficulties faced by enterprises when applying loan. |
| format | Article |
| id | doaj-art-741e28cf86974c6a96bfca50a9e84e37 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2018-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-741e28cf86974c6a96bfca50a9e84e372025-02-03T01:10:22ZengWileyComplexity1076-27871099-05262018-01-01201810.1155/2018/10326431032643A Novel Approach for Reducing Attributes and Its Application to Small Enterprise Financing Ability EvaluationBaofeng Shi0Bin Meng1Hufeng Yang2Jing Wang3Wenli Shi4College of Economics & Management, Northwest A&F University, Yangling, Shaanxi 712100, ChinaCollaborative Innovation Center for Transport Studies, Dalian Maritime University, Dalian, Liaoning 116026, ChinaCollege of Economics & Management, Northwest A&F University, Yangling, Shaanxi 712100, ChinaCollege of Economics & Management, Northwest A&F University, Yangling, Shaanxi 712100, ChinaSchool of Management Engineering and Business, Hebei University of Engineering, Handan, Hebei 056038, ChinaAttribute reduction is viewed as a kind of preprocessing steps for reducing large dimensionality in data mining of all complex systems. A great deal of researchers have proposed various approaches to reduce attributes or select key features in multicriteria decision making evaluation. In practice, the existing approaches for attribute reduction focused on improving the classification accuracy or saving the cost of computational time, without considering the influence of the reduction results on the original data set. To help address this gap, we develop an advanced novel attribute reduction approach combining Pearson correlation analysis with F test significance discrimination for the screening and identification of key characteristics related to the original data set. The proposed model has been verified using the financing ability evaluation data of 713 small enterprises of a city commercial bank in China. And the experimental results show that the proposed reduction model is efficient and effective. Moreover, our experimental findings help to locate the qualified partners and alleviate the difficulties faced by enterprises when applying loan.http://dx.doi.org/10.1155/2018/1032643 |
| spellingShingle | Baofeng Shi Bin Meng Hufeng Yang Jing Wang Wenli Shi A Novel Approach for Reducing Attributes and Its Application to Small Enterprise Financing Ability Evaluation Complexity |
| title | A Novel Approach for Reducing Attributes and Its Application to Small Enterprise Financing Ability Evaluation |
| title_full | A Novel Approach for Reducing Attributes and Its Application to Small Enterprise Financing Ability Evaluation |
| title_fullStr | A Novel Approach for Reducing Attributes and Its Application to Small Enterprise Financing Ability Evaluation |
| title_full_unstemmed | A Novel Approach for Reducing Attributes and Its Application to Small Enterprise Financing Ability Evaluation |
| title_short | A Novel Approach for Reducing Attributes and Its Application to Small Enterprise Financing Ability Evaluation |
| title_sort | novel approach for reducing attributes and its application to small enterprise financing ability evaluation |
| url | http://dx.doi.org/10.1155/2018/1032643 |
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