Automated machine learning with dynamic ensemble selection-Reference-Cited by-同舟云学术

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Automated machine learning with dynamic ensemble selection

Published:2023-07-13 Issue:20 Volume:53 Page:23596-23612
ISSN:0924-669X
Container-title:Applied Intelligence
language:en
Short-container-title:Appl Intell

Author:

Zhu Xiaoyan^ORCID,Ren Jingtao,Wang Jiayin,Li Jiaxuan

Publisher

Springer Science and Business Media LLC

Subject

Artificial Intelligence

Link

https://link.springer.com/content/pdf/10.1007/s10489-023-04770-7.pdf

Reference54 articles.

1. Bergstra J, Bardenet R, Bengio Y, et al (2011) Algorithms for hyper-parameter optimization. Advances in neural information processing systems 24

2. Bergstra J, Yamins D, Cox DD, et al (2013) Hyperopt: A python library for optimizing the hyperparameters of machine learning algorithms. In: Proceedings of the 12th Python in science conference, Citeseer, p 20

3. Brodersen KH, Ong CS, Stephan KE, et al (2010) The balanced accuracy and its posterior distribution. In: 2010 20th international conference on pattern recognition, IEEE, pp 3121–3124

4. Brun AL, Britto AS, Oliveira LS, et al (2016) Contribution of data complexity features on dynamic classifier selection. In: 2016 International Joint Conference on Neural Networks (IJCNN), IEEE, pp 4396–4403

5. Caruana R, Niculescu-Mizil A, Crew G, et al (2004) Ensemble selection from libraries of models. In: Proceedings of the twenty-first international conference on Machine learning, p 18

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