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Kernel-based data fusion for machine learning : methods and applications in bioinformatics and text mining

Author: Shi Yu
Publisher: New York : Springer, 2011.
Series: Studies in computational intelligence, v. 345.
Edition/Format:   eBook : Document : EnglishView all editions and formats
Database:WorldCat
Summary:

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  Read more...

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Genre/Form: Electronic books
Additional Physical Format: Print version:
Yu, Shi.
Kernel-based data fusion for machine learning.
New York : Springer, 2011
(DLC) 2011923523
Material Type: Document, Internet resource
Document Type: Internet Resource, Computer File
All Authors / Contributors: Shi Yu
ISBN: 9783642194061 3642194060
OCLC Number: 726826787
Description: 1 online resource (xiv, 212 pages) : illustrations (some color).
Contents: Introduction.- 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.
Series Title: Studies in computational intelligence, v. 345.
Responsibility: Shi Yu [and others].

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From the reviews: "The book provides an introduction to data fusion problems using support vector machines (SVMs). ... The book is meant for researchers, scientists and engineers using SVMs, or other Read more...

 
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