Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods
Language: English
Published by Springer, Palgrave Macmillan Dez 2018, 2018
Series: Book 312 of 538 - Studies in Computational Intelligence
- Hardcover
- New
Seller: buchversandmimpf2000, Emtmannsberg, BAYE, Germanybuchversandmimpf2000
AbeBooks seller since January 23, 2017
Condition: New
£ 94.62
Quantity: 1 available
Add to basketItem description from seller
This item is printed on demand - Print on Demand Titel. Neuware -This book presents novel classification algorithms for four challenging prediction tasks, namely learning from imbalanced, semi-supervised, multi-instance and multi-label data. The methods are based on fuzzy rough set theory, a mathematical framework used to model uncertainty in data. The book makes two main contributions: helping readers gain a deeper understanding of the underlying mathematical theory; and developing new, intuitive and well-performing classification approaches. The authors bridge the gap between the theoretical proposals of the mathematical model and important challenges in machine learning.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 268 pp. Englisch.
Seller Inventory # 9783030046620
- Title
- Dealing with Imbalanced and Weakly Labelled Data in Machine Learning using Fuzzy and Rough Set Methods
- Author
- Sarah Vluymans
- Publisher
- Springer, Palgrave Macmillan Dez 2018
- Publication year
- 2018
- Condition
- Neu
- Binding
- Buch
- Language
- English
- ISBN 10
- 3030046621
- ISBN 13
- 9783030046620
- Item weight
- 571 grams
- Dimensions
- 241x160x21 mm
- Series
- Book 312 of 538: Studies in Computational Intelligence
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buchversandmimpf2000
Emtmannsberg, BAYE, Germany
AbeBooks seller since January 23, 2017
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Impressum Thorsten Retsch Buchversand Mimpf2000 Oberölschnitz 16 95517 Emtmannsberg Deutschland Telefon: 09209-2023188 Email: mimpf2000@online.de USt-ID-Nr.: DE 235096871 Wir führen gebrauchte Bücher aus allen Sparten der Literatur
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