An Empirical Analysis of Integrating Feature Extraction to Automated Machine Learning Pipeline-Reference-Cited by-同舟云学术

An Empirical Analysis of Integrating Feature Extraction to Automated Machine Learning Pipeline

Published:2021 Issue: Volume: Page:336-344
ISSN:0302-9743
Container-title:Pattern Recognition. ICPR International Workshops and Challenges
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Author:

Eldeeb Hassan,Amashukeli Shota,El Shawi Radwa

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-030-68799-1_24

Reference22 articles.

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2. Fan, W., et al.: Generalized and heuristic-free feature construction for improved accuracy. In: Proceedings of the 2010 SIAM International Conference on Data Mining, pp. 629–640. SIAM (2010)

3. Feurer, M., Eggensperger, K., Falkner, S., Lindauer, M., Hutter, F.: Auto-sklearn 2.0: The next generation (2020). arXiv preprint arXiv:2007.04074

4. Feurer, M., Klein, A., Eggensperger, K., Springenberg, J., Blum, M., Hutter, F.: Efficient and robust automated machine learning. In: Advances in Neural Information Processing Systems, pp. 2962–2970 (2015)

5. Gaudel, R., Sebag, M.: Feature selection as a one-player game (2010)

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