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Dataset complexity assessment based on cumulative maximum scaled area under Laplacian spectrum
Title: | Dataset complexity assessment based on cumulative maximum scaled area under Laplacian spectrum |
Authors: | Li, Guang Browse this author | Togo, Ren Browse this author | Ogawa, Takahiro Browse this author →KAKEN DB | Haseyama, Miki Browse this author →KAKEN DB |
Keywords: | Dataset complexity assessment | Classification problem | Laplacian spectrum | Spectral clustering |
Issue Date: | 13-Apr-2022 |
Publisher: | Springer |
Journal Title: | Multimedia Tools and Applications |
Volume: | 81 |
Issue: | 22 |
Start Page: | 32287 |
End Page: | 32303 |
Publisher DOI: | 10.1007/s11042-022-13027-3 |
Abstract: | Dataset complexity assessment aims to predict classification performance on a dataset with complexity calculation before training a classifier, which can also be used for classifier selection and dataset reduction. The training process of deep convolutional neural networks (DCNNs) is iterative and time-consuming because of hyperparameter uncertainty and the domain shift introduced by different datasets. Hence, it is meaningful to predict classification performance by assessing the complexity of datasets effectively before training DCNN models. This paper proposes a novel method called cumulative maximum scaled Area Under Laplacian Spectrum (cmsAULS), which can achieve state-of-the-art complexity assessment performance on six datasets. |
Rights: | This version of the article has been accepted for publication, after peer review (when applicable) and is subject to Springer Nature’s AM terms of use, but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1007/s11042-022-13027-3 |
Type: | article (author version) |
URI: | http://hdl.handle.net/2115/88977 |
Appears in Collections: | 情報科学院・情報科学研究院 (Graduate School of Information Science and Technology / Faculty of Information Science and Technology) > 雑誌発表論文等 (Peer-reviewed Journal Articles, etc)
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Submitter: Li Guang(李 広)
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