Complexity

Complexity / 2021 / Article
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Machine Learning Applications in Complex Economics and Financial Networks

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Corrigendum | Open Access

Volume 2021 |Article ID 9865171 | https://doi.org/10.1155/2021/9865171

Ying Chen, Ruirui Zhang, "Corrigendum to “Research on Credit Card Default Prediction Based on -Means SMOTE and BP Neural Network”", Complexity, vol. 2021, Article ID 9865171, 1 page, 2021. https://doi.org/10.1155/2021/9865171

Corrigendum to “Research on Credit Card Default Prediction Based on -Means SMOTE and BP Neural Network”

Received31 May 2021
Accepted31 May 2021
Published14 Jun 2021

In the article titled “Research on Credit Card Default Prediction Based on k-Means SMOTE and BP Neural Network” [1], the authors would like to clarify that they employed the python package, kmeans-smote 0.1.2, in this study [2]. The error is that a citation to the related article was not included in the original publication, and the following text in Section 3 should be replaced with the addition of the missing references, 22 and 23 [2, 3]:

“Therefore, according to the problem of imbalance of credit card sample categories, this paper uses an improved smote algorithm called k-means SMOTE algorithm” should be replaced with “Therefore, according to the problem of imbalance of credit card sample categories, this paper uses an improved smote algorithm called k-means SMOTE algorithm [22, 23].”

Conflicts of Interest

The authors declare that they have no conflicts of interest.

References

  1. Y. Chen and R. Zhang, “Research on Credit Card Default Prediction Based on k-Means SMOTE and BP Neural Network,” Complexity, vol. 2021, Article ID 6618841, 13 pages, 2021. View at: Publisher Site | Google Scholar
  2. G. Douzas, F. Bacao, and F. Last, “Oversampling for imbalanced learning based on k-means and SMOTE,” 2018, https://arxiv.org/abs/1711.00837. View at: Google Scholar
  3. G. Douzas, F. Bacao, and F. Last, “Improving imbalanced learning through a heuristic oversampling method based on k-means and SMOTE,” Information Sciences, vol. 465, pp. 1–20, 2018. View at: Publisher Site | Google Scholar

Copyright © 2021 Ying Chen and Ruirui Zhang. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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