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Minimum Error Entropy Classification
Details
This book explains the minimum error entropy (MEE) concept applied to data classification machines. Discusses theoretical results, offers a clustering algorithm using a MEE-like concept, and includes tests, evaluation experiments and comparative applications.
Presents data classification methodologies based on a minimum error entropy approach Includes both theoretical results and applications to real world datasets Written by leading experts in the field
Autorentext
Luís Silva, anthropologist, is Post-Doctoral research fellow at the Centre for Research in Anthropology, Universidade Nova de Lisboa (CRIA/FCSHUNL), Lisbon, Portugal. His principal research interests include rural dynamics and the anthropology of tourism, focusing specifically on the making of heritage and tourism products in rural areas, as well as on the local impact of tourism and the heritage enterprise.
Inhalt
Introduction.- Continuous Risk Functionals.- MEE with Continuous Errors.- MEE with Discrete Errors.- EE-Inspired Risks.- Applications.
Weitere Informationen
- Allgemeine Informationen
- GTIN 09783642290282
- Auflage 2013
- Schöpfer Joaquim P. Marques de Sá, Luís Silva, Jorge M. F. Santos, Luís A. Alexandre
- Sprache Englisch
- Genre Allgemeines & Lexika
- Lesemotiv Verstehen
- Größe H241mm x B160mm x T20mm
- Jahr 2012
- EAN 9783642290282
- Format Fester Einband
- ISBN 3642290280
- Veröffentlichung 25.07.2012
- Titel Minimum Error Entropy Classification
- Autor Joaquim P. Marques de Sá , Luís A. Alexandre , Jorge M. F. Santos , Luís M. A. Silva
- Untertitel Studies in Computational Intelligence 420
- Gewicht 588g
- Herausgeber Springer Berlin Heidelberg
- Anzahl Seiten 280