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.

Von der hinteren Coverseite

��ber diesen Titel� kann sich auf eine andere Ausgabe dieses Titels beziehen.

Anbieterinformationen

Zur Homepage des Verk�ufers

Unternehmensdaten des Verk�ufers

Edward Bowditch Ltd
Exstowe, Exton, Exeter, EX3 0PP, United Kingdom

Gesch�ftsbedingungen und Versandinformationen

Verkaufsbedingungen

Legal entity name: Edward Bowditch Ltd
Legal entity form: Limited company
Business correspondence address: Exstowe, Exton, Exeter, EX3 0PP
Company registration number: 04916632
VAT registration: GB834241546
Authorised representative: Mr. E. Bowditch