Uncertainty Modeling for Data Mining A Label Semantics Approach /

Uncertainty Modeling for Data Mining A Label Semantics Approach /

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 un...

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Bibliographic Details
Published in:Springer eBooks
Main Authors: Qin, Zengchang (Author), Tang, Yongchuan (Author)
Corporate Author: SpringerLink (Online service)
Format: eBook
Language:English
Published: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2014.
Series:Advanced Topics in Science and Technology in China,
Subjects:
Computer Science.
Information systems.
Data mining.
Artificial intelligence.
Data Mining and Knowledge Discovery.
Artificial Intelligence (incl. Robotics).
Information Systems and Communication Service.
Math Applications in Computer Science.
Online Access:http://dx.doi.org/10.1007/978-3-642-41251-6
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http://dx.doi.org/10.1007/978-3-642-41251-6
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