Kernel-Based Data Fusion for Machine Learning: Methods and Applications in Bioinformatics and Text Mining

By Bart Moor, Shi Yu, Yves Moreau, et al.

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.

• Format: Paperback
• Language: English
• ISBN: 3642267513
• ISBN13: 9783642267512
• Release Date: April 2013
• Publisher: Springer
• Length: 214 Pages
• Weight: 0.72 lbs.
• Dimensions: 0.5" x 6.1" x 9.2"