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Nonlinear Dimensionality Reduction (Information Science and Statistics) John A. Lee Price: $79.95 Release Date: April 1£¬2007 Book Description Methods of dimensionality reduction provide a way to understand and visualize the structure of complex data sets. Traditional methods like principal component analysis and classical metric multidimensional scaling suffer from being based on linear models. Until recently, very few methods were able to reduce the data dimensionality in a nonlinear way. However, since the late nineties, many new methods have been developed and nonlinear dimensionality reduction, also called manifold learning, has become a hot topic. New advances that account for this rapid growth are, e.g. the use of graphs to represent the manifold topology, and the use of new metrics like the geodesic distance. In addition, new optimization schemes, based on kernel ... Read more [ Last edited by mainpro on 2007-10-4 at 20:36 ] |
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