Dimension Reduction: A Guided Tour

by Christopher J. C. Burges

We give a tutorial overview of several foundational methods for dimension reduction. We divide the methods into projective methods and methods that model the manifold on which the data lies. For projective methods, we review projection pursuit, principal component analysis (PCA), kernel PCA, probabilistic PCA, canonical correlation analysis (CCA), kernel CCA, Fisher discriminant analysis, oriented PCA, and several techniques for sufficient dimension...

• Format: Paperback
• Language: English
• ISBN: 1601983786
• ISBN13: 9781601983787
• Release Date: August 2010
• Publisher: Now Publishers
• Length: 106 Pages
• Weight: 0.35 lbs.
• Dimensions: 0.2" x 6.1" x 9.2"