Establishment of the Credit Indicator System of Micro Enterprises Based on Support Vector Machine and R-Type Clustering

The micro enterprises’ credit indicators with credit identification ability are selected by the two classification models of Support Vector Machine for the first round of indicator selection and then for the second round of indicator selection, deleting credit indicators with redundant information b...

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Main Authors: Zhanjiang Li, Chengrong Yang
Format: Article
Language:English
Published: Hindawi Limited 2018-01-01
Series:Mathematical Problems in Engineering
Online Access:http://dx.doi.org/10.1155/2018/6390720
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spelling doaj-71731659caef42718623fe7692862adc2020-11-24T21:44:24ZengHindawi LimitedMathematical Problems in Engineering1024-123X1563-51472018-01-01201810.1155/2018/63907206390720Establishment of the Credit Indicator System of Micro Enterprises Based on Support Vector Machine and R-Type ClusteringZhanjiang Li0Chengrong Yang1College of Economics and Management, Inner Mongolia Agricultural University, No. 306 Zhaowuda Road, Saihan District, Hohhot, ChinaCollege of Economics and Management, Inner Mongolia Agricultural University, No. 306 Zhaowuda Road, Saihan District, Hohhot, ChinaThe micro enterprises’ credit indicators with credit identification ability are selected by the two classification models of Support Vector Machine for the first round of indicator selection and then for the second round of indicator selection, deleting credit indicators with redundant information by clustering variables through the principle of minimum sum of deviation squares. This paper provides a screening model for credit evaluation indicators of micro enterprises and uses credit data of 860 micro enterprises samples in Inner Mongolia in western China for application analysis. The test results show that, first, the constructed final micro enterprises’ credit indicator system is in line with the 5C model; second, the validity test based on the ROC (Receiver Operating Characteristic) curve reveals that each of the screened credit evaluation indicators is valid.http://dx.doi.org/10.1155/2018/6390720
collection DOAJ
language English
format Article
sources DOAJ
author Zhanjiang Li
Chengrong Yang
spellingShingle Zhanjiang Li
Chengrong Yang
Establishment of the Credit Indicator System of Micro Enterprises Based on Support Vector Machine and R-Type Clustering
Mathematical Problems in Engineering
author_facet Zhanjiang Li
Chengrong Yang
author_sort Zhanjiang Li
title Establishment of the Credit Indicator System of Micro Enterprises Based on Support Vector Machine and R-Type Clustering
title_short Establishment of the Credit Indicator System of Micro Enterprises Based on Support Vector Machine and R-Type Clustering
title_full Establishment of the Credit Indicator System of Micro Enterprises Based on Support Vector Machine and R-Type Clustering
title_fullStr Establishment of the Credit Indicator System of Micro Enterprises Based on Support Vector Machine and R-Type Clustering
title_full_unstemmed Establishment of the Credit Indicator System of Micro Enterprises Based on Support Vector Machine and R-Type Clustering
title_sort establishment of the credit indicator system of micro enterprises based on support vector machine and r-type clustering
publisher Hindawi Limited
series Mathematical Problems in Engineering
issn 1024-123X
1563-5147
publishDate 2018-01-01
description The micro enterprises’ credit indicators with credit identification ability are selected by the two classification models of Support Vector Machine for the first round of indicator selection and then for the second round of indicator selection, deleting credit indicators with redundant information by clustering variables through the principle of minimum sum of deviation squares. This paper provides a screening model for credit evaluation indicators of micro enterprises and uses credit data of 860 micro enterprises samples in Inner Mongolia in western China for application analysis. The test results show that, first, the constructed final micro enterprises’ credit indicator system is in line with the 5C model; second, the validity test based on the ROC (Receiver Operating Characteristic) curve reveals that each of the screened credit evaluation indicators is valid.
url http://dx.doi.org/10.1155/2018/6390720
work_keys_str_mv AT zhanjiangli establishmentofthecreditindicatorsystemofmicroenterprisesbasedonsupportvectormachineandrtypeclustering
AT chengrongyang establishmentofthecreditindicatorsystemofmicroenterprisesbasedonsupportvectormachineandrtypeclustering
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