Uncertainty Modeling for Data Mining: A Label Semantics Approach (Advanced Topics in Science and Technology in China) - Hardcover

Qin, Zengchang; Tang, Yongchuan

 
9783642412509: Uncertainty Modeling for Data Mining: A Label Semantics Approach (Advanced Topics in Science and Technology in China)
Hardcover
ISBN 10: 3642412505 ISBN 13: 9783642412509
Verlag: Springer, 2014

Inhaltsangabe

Machine learning and data mining are inseparably connected with uncertainty. The observable data for learning is usually imprecise, incomplete or noisy. Uncertainty Modeling for Data Mining: A Label Semantics Approach introduces 'label semantics', a fuzzy-logic-based theory for modeling uncertainty. Several new data mining algorithms based on label semantics are proposed and tested on real-world datasets. A prototype interpretation of label semantics and new prototype-based data mining algorithms are also discussed. This book offers a valuable resource for postgraduates, researchers and other professionals in the fields of data mining, fuzzy computing and uncertainty reasoning.

Zengchang Qin is an associate professor at the School of Automation Science and Electrical Engineering, Beihang University, China; Yongchuan Tang is an associate professor at the College of Computer Science, Zhejiang University, China.

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Von der hinteren Coverseite

Machine learning and data mining are inseparably connected with uncertainty. The observable data for learning is usually imprecise, incomplete or noisy. Uncertainty Modeling for Data Mining: A Label Semantics Approach introduces 'label semantics', a fuzzy-logic-based theory for modeling uncertainty. Several new data mining algorithms based on label semantics are proposed and tested on real-world datasets. A prototype interpretation of label semantics and new prototype-based data mining algorithms are also discussed. This book offers a valuable resource for postgraduates, researchers and other professionals in the fields of data mining, fuzzy computing and uncertainty reasoning.

Zengchang Qin is an associate professor at the School of Automation Science and Electrical Engineering, Beihang University, China; Yongchuan Tang is an associate professor at the College of Computer Science, Zhejiang University, China.

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Verlag
Springer
Erscheinungsdatum
2014
Sprache
Englisch
ISBN 10 
3642412505
ISBN 13 
9783642412509
Einband
Gebundene Ausgabe
Anzahl der Seiten
310
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