New Fuzzy Support Vector Machine for the Class Imbalance Problem in Medical Datasets Classification
In medical datasets classification, support vector machine (SVM) is considered to be one of the most successful methods. However, most of the real-world medical datasets usually contain some outliers/noise and data often have class imbalance problems. In this paper, a fuzzy support machine (FSVM) fo...
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| Format: | Article |
| Language: | English |
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Wiley
2014-01-01
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| Series: | The Scientific World Journal |
| Online Access: | http://dx.doi.org/10.1155/2014/536434 |
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| _version_ | 1832549194430152704 |
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| author | Xiaoqing Gu Tongguang Ni Hongyuan Wang |
| author_facet | Xiaoqing Gu Tongguang Ni Hongyuan Wang |
| author_sort | Xiaoqing Gu |
| collection | DOAJ |
| description | In medical datasets classification, support vector machine (SVM) is considered to be one of the most successful methods. However, most of the real-world medical datasets usually contain some outliers/noise and data often have class imbalance problems. In this paper, a fuzzy support machine (FSVM) for the class imbalance problem (called FSVM-CIP) is presented, which can be seen as a modified class of FSVM by extending manifold regularization and assigning two misclassification costs for two classes. The proposed FSVM-CIP can be used to handle the class imbalance problem in the presence of outliers/noise, and enhance the locality maximum margin. Five real-world medical datasets, breast, heart, hepatitis, BUPA liver, and pima diabetes, from the UCI medical database are employed to illustrate the method presented in this paper. Experimental results on these datasets show the outperformed or comparable effectiveness of FSVM-CIP. |
| format | Article |
| id | doaj-art-c9c845a4e6d14bb3b3af34adaccea674 |
| institution | Kabale University |
| issn | 2356-6140 1537-744X |
| language | English |
| publishDate | 2014-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | The Scientific World Journal |
| spelling | doaj-art-c9c845a4e6d14bb3b3af34adaccea6742025-02-03T06:12:06ZengWileyThe Scientific World Journal2356-61401537-744X2014-01-01201410.1155/2014/536434536434New Fuzzy Support Vector Machine for the Class Imbalance Problem in Medical Datasets ClassificationXiaoqing Gu0Tongguang Ni1Hongyuan Wang2School of Information Science and Engineering, Changzhou University, Changzhou 213164, ChinaSchool of Information Science and Engineering, Changzhou University, Changzhou 213164, ChinaSchool of Information Science and Engineering, Changzhou University, Changzhou 213164, ChinaIn medical datasets classification, support vector machine (SVM) is considered to be one of the most successful methods. However, most of the real-world medical datasets usually contain some outliers/noise and data often have class imbalance problems. In this paper, a fuzzy support machine (FSVM) for the class imbalance problem (called FSVM-CIP) is presented, which can be seen as a modified class of FSVM by extending manifold regularization and assigning two misclassification costs for two classes. The proposed FSVM-CIP can be used to handle the class imbalance problem in the presence of outliers/noise, and enhance the locality maximum margin. Five real-world medical datasets, breast, heart, hepatitis, BUPA liver, and pima diabetes, from the UCI medical database are employed to illustrate the method presented in this paper. Experimental results on these datasets show the outperformed or comparable effectiveness of FSVM-CIP.http://dx.doi.org/10.1155/2014/536434 |
| spellingShingle | Xiaoqing Gu Tongguang Ni Hongyuan Wang New Fuzzy Support Vector Machine for the Class Imbalance Problem in Medical Datasets Classification The Scientific World Journal |
| title | New Fuzzy Support Vector Machine for the Class Imbalance Problem in Medical Datasets Classification |
| title_full | New Fuzzy Support Vector Machine for the Class Imbalance Problem in Medical Datasets Classification |
| title_fullStr | New Fuzzy Support Vector Machine for the Class Imbalance Problem in Medical Datasets Classification |
| title_full_unstemmed | New Fuzzy Support Vector Machine for the Class Imbalance Problem in Medical Datasets Classification |
| title_short | New Fuzzy Support Vector Machine for the Class Imbalance Problem in Medical Datasets Classification |
| title_sort | new fuzzy support vector machine for the class imbalance problem in medical datasets classification |
| url | http://dx.doi.org/10.1155/2014/536434 |
| work_keys_str_mv | AT xiaoqinggu newfuzzysupportvectormachinefortheclassimbalanceprobleminmedicaldatasetsclassification AT tongguangni newfuzzysupportvectormachinefortheclassimbalanceprobleminmedicaldatasetsclassification AT hongyuanwang newfuzzysupportvectormachinefortheclassimbalanceprobleminmedicaldatasetsclassification |