A Novel Fuzzy Kernel Extreme Learning Machine Algorithm in Classification Problems
Today, numerous methods have been developed to address various problems, each with its own advantages and limitations. To overcome these limitations, hybrid structures that integrate multiple techniques have emerged as effective computational methods, offering superior performance and efficiency com...
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MDPI AG
2025-04-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/15/8/4506 |
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| author | Asli Kaya Karakutuk Ozer Ozdemir |
| author_facet | Asli Kaya Karakutuk Ozer Ozdemir |
| author_sort | Asli Kaya Karakutuk |
| collection | DOAJ |
| description | Today, numerous methods have been developed to address various problems, each with its own advantages and limitations. To overcome these limitations, hybrid structures that integrate multiple techniques have emerged as effective computational methods, offering superior performance and efficiency compared to single-method solutions. In this paper, we introduce a basic method that combines the strengths of fuzzy logic, wavelet theory, and kernel-based extreme learning machines to efficiently classify facial expressions. We call this method the Fuzzy Wavelet Mexican Hat Kernel Extreme Learning Machine. To evaluate the classification performance of this mathematically defined hybrid method, we apply it to both an original dataset and the JAFFE dataset. The method is enhanced with various feature extraction methods. On the JAFFE dataset, the algorithm achieved an average classification accuracy of 94.55% when supported with local binary patterns and 94.27% with a histogram of oriented gradients. Moreover, these results outperform those of previous studies conducted on the same dataset. On the original dataset, the proposed method was compared with an extreme learning machine and wavelet neural network, and it was found that the method has remarkable efficiency compared to the other two methods. |
| format | Article |
| id | doaj-art-9aad6ff4ebaa4db1a691bcb960cd61f0 |
| institution | OA Journals |
| issn | 2076-3417 |
| language | English |
| publishDate | 2025-04-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj-art-9aad6ff4ebaa4db1a691bcb960cd61f02025-08-20T02:28:40ZengMDPI AGApplied Sciences2076-34172025-04-01158450610.3390/app15084506A Novel Fuzzy Kernel Extreme Learning Machine Algorithm in Classification ProblemsAsli Kaya Karakutuk0Ozer Ozdemir1Rectorate, 2 Eylul Campus, Eskisehir Technical University, 26555 Eskisehir, TürkiyeDepartment of Statistics, Science Faculty, Eskisehir Technical University, 26470 Eskisehir, TürkiyeToday, numerous methods have been developed to address various problems, each with its own advantages and limitations. To overcome these limitations, hybrid structures that integrate multiple techniques have emerged as effective computational methods, offering superior performance and efficiency compared to single-method solutions. In this paper, we introduce a basic method that combines the strengths of fuzzy logic, wavelet theory, and kernel-based extreme learning machines to efficiently classify facial expressions. We call this method the Fuzzy Wavelet Mexican Hat Kernel Extreme Learning Machine. To evaluate the classification performance of this mathematically defined hybrid method, we apply it to both an original dataset and the JAFFE dataset. The method is enhanced with various feature extraction methods. On the JAFFE dataset, the algorithm achieved an average classification accuracy of 94.55% when supported with local binary patterns and 94.27% with a histogram of oriented gradients. Moreover, these results outperform those of previous studies conducted on the same dataset. On the original dataset, the proposed method was compared with an extreme learning machine and wavelet neural network, and it was found that the method has remarkable efficiency compared to the other two methods.https://www.mdpi.com/2076-3417/15/8/4506hybrid algorithmsfacial expressionsclassificationwavelet kernelextreme learning machine |
| spellingShingle | Asli Kaya Karakutuk Ozer Ozdemir A Novel Fuzzy Kernel Extreme Learning Machine Algorithm in Classification Problems Applied Sciences hybrid algorithms facial expressions classification wavelet kernel extreme learning machine |
| title | A Novel Fuzzy Kernel Extreme Learning Machine Algorithm in Classification Problems |
| title_full | A Novel Fuzzy Kernel Extreme Learning Machine Algorithm in Classification Problems |
| title_fullStr | A Novel Fuzzy Kernel Extreme Learning Machine Algorithm in Classification Problems |
| title_full_unstemmed | A Novel Fuzzy Kernel Extreme Learning Machine Algorithm in Classification Problems |
| title_short | A Novel Fuzzy Kernel Extreme Learning Machine Algorithm in Classification Problems |
| title_sort | novel fuzzy kernel extreme learning machine algorithm in classification problems |
| topic | hybrid algorithms facial expressions classification wavelet kernel extreme learning machine |
| url | https://www.mdpi.com/2076-3417/15/8/4506 |
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