Bibliografie

Detailansicht

Kernel-based Data Fusion for Machine Learning

Methods and Applications in Bioinformatics and Text Mining, Studies in Computational Intelligence 345
Yu, Shi/Tranchevent, Léon-Charles/Moor, Bart et al
Springer Verlag GmbH
ISBN/EAN: 9783642267512
Umbreit-Nr.: 4624240

Sprache: Englisch
Umfang: xiv, 214 S., 41 s/w Illustr., 2 farbige Illustr.
Format in cm:
Einband: kartoniertes Buch

Erschienen am 21.04.2013
Auflage: 1/2013
€ 181,89
(inklusive MwSt.)
Lieferbar innerhalb 1 - 2 Wochen
Beim Buchhandel bestellen
  • Zusatztext

    • InhaltsangabeIntroduction.- Rayleigh quotient-type problems in machine learning.- Ln-norm Multiple Kernel Learning and Least Squares Support VectorMachines.- Optimized data fusion for kernel k-means Clustering.- Multi-view text mining for disease gene prioritization and clustering.- Optimized data fusion for k-means Laplacian Clustering.- Weighted Multiple Kernel Canonical Correlation.- Cross-species candidate gene prioritization with MerKator.- Conclusion.

  • Kurztext

    • Data fusion problems arise in many different fields. This book provides a specific introduction to solve data fusion problems using support vector machines. The reader will require a good knowledge of data mining, machine learning and linear algebra.