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Using meta-learning for automated algorithms selection and configuration: an experimental framework for industrial big data

Overview of attention for article published in Journal of Big Data, April 2022
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67 Mendeley
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Title
Using meta-learning for automated algorithms selection and configuration: an experimental framework for industrial big data
Published in
Journal of Big Data, April 2022
DOI 10.1186/s40537-022-00612-4
Authors

Moncef Garouani, Adeel Ahmad, Mourad Bouneffa, Mohamed Hamlich, Gregory Bourguin, Arnaud Lewandowski

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 67 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 67 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 6 9%
Student > Postgraduate 3 4%
Student > Master 3 4%
Student > Bachelor 3 4%
Lecturer 2 3%
Other 10 15%
Unknown 40 60%
Readers by discipline Count As %
Engineering 11 16%
Computer Science 10 15%
Agricultural and Biological Sciences 2 3%
Unspecified 2 3%
Environmental Science 1 1%
Other 4 6%
Unknown 37 55%