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In den WarenkorbZustand: New. In.
Sprache: Englisch
Verlag: Springer-Verlag New York Inc, 2018
ISBN 10: 3319961322 ISBN 13: 9783319961323
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
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In den WarenkorbPaperback. Zustand: Brand New. 504 pages. 9.25x6.10x1.26 inches. In Stock.
Zustand: New.
Taschenbuch. Zustand: Neu. Machine Learning and Data Mining in Pattern Recognition | 14th International Conference, MLDM 2018, New York, NY, USA, July 15-19, 2018, Proceedings, Part II | Petra Perner | Taschenbuch | Lecture Notes in Computer Science | xv | Englisch | 2018 | Springer | EAN 9783319961323 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu.
Taschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This two-volume set LNAI 10934 and LNAI 10935 constitutes the refereed proceedings of the 14th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2018, held in New York, NY, USA in July 2018.The 92 regular papers presented in this two-volume set were carefully reviewed and selected from 298 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.
Zustand: Hervorragend. Zustand: Hervorragend | Seiten: 504 | Sprache: Englisch | Produktart: Bücher | This two-volume set LNAI 10934 and LNAI 10935 constitutes the refereed proceedings of the 14th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2018, held in New York, NY, USA in July 2018. The 92 regular papers presented in this two-volume set were carefully reviewed and selected from 298 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multi-media data types such as image mining, text mining, video mining, and Web mining.