Principal Manifolds for Data Visualization and Dimension Reduction (Lecture Notes in Computational Science and Engineering)

by Donald C . Wunsch (Editor), Alexander N . Gorban (Editor), Balázs Kégl (Editor), Andrei Zinovyev (Editor)

• New

  Paperback
  2007

  $228.57

  The book starts with the quote of the classical Pearson definition of PCA and includes reviews of various methods: NLPCA, ICA, MDS, embedding and clustering algorithms, principal manifolds and SOM. New approaches to NLPCA, principal manifolds, branching principal components and topology preserving mappings are described.