Open Access
Procedia Computer Science, volume 193, pages 484-493
Sensitivity Analysis of the Composite Data-Driven Pipelines in the Automated Machine Learning
Publication type: Journal Article
Publication date: 2021-11-19
Journal:
Procedia Computer Science
Quartile SCImago
— Quartile WOS
—
Impact factor: —
ISSN: 18770509
General Medicine
Citations by journals
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International Journal of Data Science and Analytics
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International Journal of Data Science and Analytics
1 publication, 50%
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IEEE Access
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IEEE Access
1 publication, 50%
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1
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Citations by publishers
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Springer Nature
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Springer Nature
1 publication, 50%
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IEEE
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IEEE
1 publication, 50%
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1
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- We do not take into account publications that without a DOI.
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Barabanova I. V., Vychuzhanin P., Nikitin N. O. Sensitivity Analysis of the Composite Data-Driven Pipelines in the Automated Machine Learning // Procedia Computer Science. 2021. Vol. 193. pp. 484-493.
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Barabanova I. V., Vychuzhanin P., Nikitin N. O. Sensitivity Analysis of the Composite Data-Driven Pipelines in the Automated Machine Learning // Procedia Computer Science. 2021. Vol. 193. pp. 484-493.
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TY - JOUR
DO - 10.1016/j.procs.2021.10.050
UR - https://doi.org/10.1016%2Fj.procs.2021.10.050
TI - Sensitivity Analysis of the Composite Data-Driven Pipelines in the Automated Machine Learning
T2 - Procedia Computer Science
AU - Barabanova, Irina V
AU - Vychuzhanin, Pavel
AU - Nikitin, Nikolay O
PY - 2021
DA - 2021/11/19 00:00:00
PB - Elsevier
SP - 484-493
VL - 193
SN - 1877-0509
ER -
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@article{2021_Barabanova,
author = {Irina V Barabanova and Pavel Vychuzhanin and Nikolay O Nikitin},
title = {Sensitivity Analysis of the Composite Data-Driven Pipelines in the Automated Machine Learning},
journal = {Procedia Computer Science},
year = {2021},
volume = {193},
publisher = {Elsevier},
month = {nov},
url = {https://doi.org/10.1016%2Fj.procs.2021.10.050},
pages = {484--493},
doi = {10.1016/j.procs.2021.10.050}
}
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