Deep Non-Parallel Hyperplane Support Vector Machine for Classification
In the last few decades, deep learning based on neural networks has become popular for the classification tasks, which combines feature extraction with the classification tasks and always achieves the satisfactory performance. Non-parallel hyperplane support vector machine (NPHSVM) aims at construct...
| Main Authors: | , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
IEEE
2023-01-01
|
| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10018402/ |
| _version_ | 1797902326683402240 |
|---|---|
| author | Feixiang Sun Xijiong Xie |
| author_facet | Feixiang Sun Xijiong Xie |
| author_sort | Feixiang Sun |
| collection | DOAJ |
| description | In the last few decades, deep learning based on neural networks has become popular for the classification tasks, which combines feature extraction with the classification tasks and always achieves the satisfactory performance. Non-parallel hyperplane support vector machine (NPHSVM) aims at constructing two non-parallel hyperplanes to classify data and extracted features are always used to be input data for NPHSVM. As for NPHSVM, extracted features will greatly influence the performance of the model to some extent. Therefore, in this paper, we propose a novel DNHSVM for classification, which combines deep feature extraction with the generation of hyperplanes seamlessly. Each hyperplane is close to its own class and as far as possible to other classes, and deep features are friendly for classification and samples are easy to be classified. Experiments on UCI datasets show the effectiveness of our proposed method, which outperforms other compared state-of-the-art algorithms. |
| first_indexed | 2024-04-10T09:14:47Z |
| format | Article |
| id | doaj.art-e17dd7f8315f46f78b9c3d091e53f355 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-04-10T09:14:47Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-e17dd7f8315f46f78b9c3d091e53f3552023-02-21T00:01:01ZengIEEEIEEE Access2169-35362023-01-01117759776710.1109/ACCESS.2023.323764110018402Deep Non-Parallel Hyperplane Support Vector Machine for ClassificationFeixiang Sun0https://orcid.org/0000-0001-9578-3316Xijiong Xie1https://orcid.org/0000-0002-5288-1861School of Information Science and Engineering, Ningbo University, Ningbo, ChinaSchool of Information Science and Engineering, Ningbo University, Ningbo, ChinaIn the last few decades, deep learning based on neural networks has become popular for the classification tasks, which combines feature extraction with the classification tasks and always achieves the satisfactory performance. Non-parallel hyperplane support vector machine (NPHSVM) aims at constructing two non-parallel hyperplanes to classify data and extracted features are always used to be input data for NPHSVM. As for NPHSVM, extracted features will greatly influence the performance of the model to some extent. Therefore, in this paper, we propose a novel DNHSVM for classification, which combines deep feature extraction with the generation of hyperplanes seamlessly. Each hyperplane is close to its own class and as far as possible to other classes, and deep features are friendly for classification and samples are easy to be classified. Experiments on UCI datasets show the effectiveness of our proposed method, which outperforms other compared state-of-the-art algorithms.https://ieeexplore.ieee.org/document/10018402/Deep learningnon-parallel hyperplane support vector machinefeature extraction |
| spellingShingle | Feixiang Sun Xijiong Xie Deep Non-Parallel Hyperplane Support Vector Machine for Classification IEEE Access Deep learning non-parallel hyperplane support vector machine feature extraction |
| title | Deep Non-Parallel Hyperplane Support Vector Machine for Classification |
| title_full | Deep Non-Parallel Hyperplane Support Vector Machine for Classification |
| title_fullStr | Deep Non-Parallel Hyperplane Support Vector Machine for Classification |
| title_full_unstemmed | Deep Non-Parallel Hyperplane Support Vector Machine for Classification |
| title_short | Deep Non-Parallel Hyperplane Support Vector Machine for Classification |
| title_sort | deep non parallel hyperplane support vector machine for classification |
| topic | Deep learning non-parallel hyperplane support vector machine feature extraction |
| url | https://ieeexplore.ieee.org/document/10018402/ |
| work_keys_str_mv | AT feixiangsun deepnonparallelhyperplanesupportvectormachineforclassification AT xijiongxie deepnonparallelhyperplanesupportvectormachineforclassification |