FlexBoost: A Flexible Boosting Algorithm With Adaptive Loss Functions
Adaptive Boosting (AdaBoost) is a representative boosting algorithm that can build a strong classifier by optimally combining weak classifiers in such a way that subsequent weak classifiers are tweaked in favor of instances misclassified by previous classifiers. However, AdaBoost is known to be susc...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8821290/ |
| _version_ | 1818323372407259136 |
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| author | Yong-Seok Jeon Dong-Hyuk Yang Dong-Joon Lim |
| author_facet | Yong-Seok Jeon Dong-Hyuk Yang Dong-Joon Lim |
| author_sort | Yong-Seok Jeon |
| collection | DOAJ |
| description | Adaptive Boosting (AdaBoost) is a representative boosting algorithm that can build a strong classifier by optimally combining weak classifiers in such a way that subsequent weak classifiers are tweaked in favor of instances misclassified by previous classifiers. However, AdaBoost is known to be susceptible to overfitting problems due to the static nature of its weight-updating process. In this paper, we propose a new boosting algorithm, named FlexBoost (Flexible AdaBoost), that can enhance classification performance by employing adaptive loss functions, i.e., by adjusting the sensitivity of the conventional (exponential) loss function for each weak classifier. The performance benchmarks on 30 binary classification problems taken from the UCI and Kaggle datasets are presented to empirically validate the proposed algorithm. |
| first_indexed | 2024-12-13T11:11:39Z |
| format | Article |
| id | doaj.art-e3202a1746d34438aa238f2464b2a94b |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-13T11:11:39Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-e3202a1746d34438aa238f2464b2a94b2022-12-21T23:48:43ZengIEEEIEEE Access2169-35362019-01-01712505412506110.1109/ACCESS.2019.29383568821290FlexBoost: A Flexible Boosting Algorithm With Adaptive Loss FunctionsYong-Seok Jeon0Dong-Hyuk Yang1Dong-Joon Lim2Systems Management Engineering Department, Sungkyunkwan University, Suwon, South KoreaSystems Management Engineering Department, Sungkyunkwan University, Suwon, South KoreaSystems Management Engineering Department, Sungkyunkwan University, Suwon, South KoreaAdaptive Boosting (AdaBoost) is a representative boosting algorithm that can build a strong classifier by optimally combining weak classifiers in such a way that subsequent weak classifiers are tweaked in favor of instances misclassified by previous classifiers. However, AdaBoost is known to be susceptible to overfitting problems due to the static nature of its weight-updating process. In this paper, we propose a new boosting algorithm, named FlexBoost (Flexible AdaBoost), that can enhance classification performance by employing adaptive loss functions, i.e., by adjusting the sensitivity of the conventional (exponential) loss function for each weak classifier. The performance benchmarks on 30 binary classification problems taken from the UCI and Kaggle datasets are presented to empirically validate the proposed algorithm.https://ieeexplore.ieee.org/document/8821290/Data miningensemble modelingboostingAdaBoostloss functionweight control |
| spellingShingle | Yong-Seok Jeon Dong-Hyuk Yang Dong-Joon Lim FlexBoost: A Flexible Boosting Algorithm With Adaptive Loss Functions IEEE Access Data mining ensemble modeling boosting AdaBoost loss function weight control |
| title | FlexBoost: A Flexible Boosting Algorithm With Adaptive Loss Functions |
| title_full | FlexBoost: A Flexible Boosting Algorithm With Adaptive Loss Functions |
| title_fullStr | FlexBoost: A Flexible Boosting Algorithm With Adaptive Loss Functions |
| title_full_unstemmed | FlexBoost: A Flexible Boosting Algorithm With Adaptive Loss Functions |
| title_short | FlexBoost: A Flexible Boosting Algorithm With Adaptive Loss Functions |
| title_sort | flexboost a flexible boosting algorithm with adaptive loss functions |
| topic | Data mining ensemble modeling boosting AdaBoost loss function weight control |
| url | https://ieeexplore.ieee.org/document/8821290/ |
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