Data-enabled analytics : DEA for big data
Year of publication: |
[2021]
|
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Other Persons: | Zhu, Joe (ed.) ; Charles, Vincent (ed.) |
Publisher: |
Cham : Springer International Publishing Cham : Imprint: Springer |
Subject: | efficiency | big data | best-practice | data envelopment analysis | data-enabled analytics | data science | forecasting | large-scale computations | performance evaluation | random forest | reinforcement learning | Big Data | Big data | Data Mining | Data mining | Operations Research | Operations research |
Description of contents: | Description [swbplus.bsz-bw.de] |
Extent: | 1 Online-Ressource (X, 364 p. 103 illus.) |
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Series: | |
Type of publication: | Book / Working Paper |
Language: | English |
ISBN: | 978-3-030-75162-3 ; 978-3-030-75161-6 ; 978-3-030-75163-0 ; 978-3-030-75164-7 |
Other identifiers: | 10.1007/978-3-030-75162-3 [DOI] |
Classification: | Informatik: Allgemeines |
Source: | ECONIS - Online Catalogue of the ZBW |
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