$$\nu $$ ν -Improved nonparallel support vector machine
Abstract In this paper, a $$\nu $$ ν -improved nonparallel support vector machine ( $$\nu $$ ν -IMNPSVM) is proposed to solve binary classification problems. In this model, we use related ideas of $$\nu $$ ν -support vector machine( $$\nu $$ ν -SVM), the parameter $$\nu $$ ν is introduced to control...
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| Format: | Article |
| Language: | English |
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Nature Portfolio
2022-10-01
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| Series: | Scientific Reports |
| Online Access: | https://doi.org/10.1038/s41598-022-22559-5 |
| _version_ | 1811197971317915648 |
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| author | Fengmin Sun Shujun Lian |
| author_facet | Fengmin Sun Shujun Lian |
| author_sort | Fengmin Sun |
| collection | DOAJ |
| description | Abstract In this paper, a $$\nu $$ ν -improved nonparallel support vector machine ( $$\nu $$ ν -IMNPSVM) is proposed to solve binary classification problems. In this model, we use related ideas of $$\nu $$ ν -support vector machine( $$\nu $$ ν -SVM), the parameter $$\nu $$ ν is introduced to control the limits of the support vectors percentage. In the objective function, the parameter $$\varepsilon $$ ε is increased to ensure that $$\varepsilon $$ ε -band is kept as small as possible. It has played a great role in the classification of unbalanced data sets. On the basis of maximizing the interval between two classes, $$\nu $$ ν -IMNPSVM can fully fit the distribution of data points in the class by minimizing the $$\varepsilon $$ ε -band, which enhances the generalization ability of the model. The results on the benchmark datasets testify that the proposed model has a good effect on the classification accuracy. |
| first_indexed | 2024-04-12T01:23:24Z |
| format | Article |
| id | doaj.art-a2e718f692d240de93a47ca3d5940af9 |
| institution | Directory Open Access Journal |
| issn | 2045-2322 |
| language | English |
| last_indexed | 2024-04-12T01:23:24Z |
| publishDate | 2022-10-01 |
| publisher | Nature Portfolio |
| record_format | Article |
| series | Scientific Reports |
| spelling | doaj.art-a2e718f692d240de93a47ca3d5940af92022-12-22T03:53:43ZengNature PortfolioScientific Reports2045-23222022-10-0112111310.1038/s41598-022-22559-5$$\nu $$ ν -Improved nonparallel support vector machineFengmin Sun0Shujun Lian1School of Management Science, Qufu Normal UniversitySchool of Management Science, Qufu Normal UniversityAbstract In this paper, a $$\nu $$ ν -improved nonparallel support vector machine ( $$\nu $$ ν -IMNPSVM) is proposed to solve binary classification problems. In this model, we use related ideas of $$\nu $$ ν -support vector machine( $$\nu $$ ν -SVM), the parameter $$\nu $$ ν is introduced to control the limits of the support vectors percentage. In the objective function, the parameter $$\varepsilon $$ ε is increased to ensure that $$\varepsilon $$ ε -band is kept as small as possible. It has played a great role in the classification of unbalanced data sets. On the basis of maximizing the interval between two classes, $$\nu $$ ν -IMNPSVM can fully fit the distribution of data points in the class by minimizing the $$\varepsilon $$ ε -band, which enhances the generalization ability of the model. The results on the benchmark datasets testify that the proposed model has a good effect on the classification accuracy.https://doi.org/10.1038/s41598-022-22559-5 |
| spellingShingle | Fengmin Sun Shujun Lian $$\nu $$ ν -Improved nonparallel support vector machine Scientific Reports |
| title | $$\nu $$ ν -Improved nonparallel support vector machine |
| title_full | $$\nu $$ ν -Improved nonparallel support vector machine |
| title_fullStr | $$\nu $$ ν -Improved nonparallel support vector machine |
| title_full_unstemmed | $$\nu $$ ν -Improved nonparallel support vector machine |
| title_short | $$\nu $$ ν -Improved nonparallel support vector machine |
| title_sort | nu ν improved nonparallel support vector machine |
| url | https://doi.org/10.1038/s41598-022-22559-5 |
| work_keys_str_mv | AT fengminsun nunimprovednonparallelsupportvectormachine AT shujunlian nunimprovednonparallelsupportvectormachine |