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Ensemble with estimation : seeking for optimization in class noisy data
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Xu, Ruifeng, Wen, Zhiyuan , Gui, Lin, Lu, Qin, Li, Binyang and Wang, Xizhao (2020) Ensemble with estimation : seeking for optimization in class noisy data. International Journal of Machine Learning and Cybernetics, 11 . pp. 231-248. doi:10.1007/s13042-019-00969-8 ISSN 1868-8071.
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WRAP-ensemble-estimation-seeking-optimization-class-noisy-data-Gui-2019.pdf - Accepted Version - Requires a PDF viewer. Download (1373Kb) | Preview |
Official URL: https://doi.org/10.1007/s13042-019-00969-8
Abstract
Class noise, as know as the mislabeled data in training set, can lead to poor accuracy in classification no matter what machine learning methods are used. A reasonable estimation of class noise has a significant impact on the performance of learning methods. However, the error in estimation is inevitable theoretically. In this work, we propose an ensemble with estimation method to overcome the gap between the estimation and true distribution of class noise. Our proposed method does not require any a priori knowledge about class noises. We prove that the optimal classifier on the noisy distribution can approximate the optimal classifier on the clean distribution when the training set grows. Comparisons with existing algorithms show that our methods outperform state-of-the-art approaches on a large number of benchmark datasets in different domains. Both the theoretical analysis and the experimental result reveal that our method can improve the performance, works well on clean data and is robust on the algorithm parameter.
Item Type: | Journal Article | ||||||||
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Divisions: | Faculty of Science, Engineering and Medicine > Science > Computer Science | ||||||||
Journal or Publication Title: | International Journal of Machine Learning and Cybernetics | ||||||||
Publisher: | Springer | ||||||||
ISSN: | 1868-8071 | ||||||||
Official Date: | February 2020 | ||||||||
Dates: |
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Volume: | 11 | ||||||||
Page Range: | pp. 231-248 | ||||||||
DOI: | 10.1007/s13042-019-00969-8 | ||||||||
Status: | Peer Reviewed | ||||||||
Publication Status: | Published | ||||||||
Reuse Statement (publisher, data, author rights): | This is a post-peer-review, pre-copyedit version of an article published in [insert journal title]. The final authenticated version is available online at: http://dx.doi.org/[insert DOI]. | ||||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||||
Date of first compliant deposit: | 31 May 2019 | ||||||||
Date of first compliant Open Access: | 12 June 2020 | ||||||||
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