In 1901, Karl Pearson invented Principal Component Analysis (PCA). Since then, PCA serves as a prototype for many other tools of data analysis, visualization and dimension reduction: Independent Component Analysis (ICA), Multidimensional Scaling (MDS), Nonlinear PCA (NLPCA), Self Organizing Maps (SOM), etc. 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 ...
Read More
In 1901, Karl Pearson invented Principal Component Analysis (PCA). Since then, PCA serves as a prototype for many other tools of data analysis, visualization and dimension reduction: Independent Component Analysis (ICA), Multidimensional Scaling (MDS), Nonlinear PCA (NLPCA), Self Organizing Maps (SOM), etc. 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 as well. Presentation of algorithms is supplemented by case studies, from engineering to astronomy, but mostly of biological data: analysis of microarray and metabolite data. The volume ends with a tutorial "PCA and K-means decipher genome". The book is meant to be useful for practitioners in applied data analysis in life sciences, engineering, physics and chemistry; it will also be valuable to PhD students and researchers in computer sciences, applied mathematics and statistics.
Read Less
Add this copy of Principal Manifolds for Data Visualization and Dim to cart. $197.73, new condition, Sold by Basi6 International rated 5.0 out of 5 stars, ships from Irving, TX, UNITED STATES, published 2007 by Springer.
Add this copy of Principal Manifolds for Data Visualization and to cart. $243.84, new condition, Sold by Ingram Customer Returns Center rated 5.0 out of 5 stars, ships from NV, USA, published 2007 by Springer.
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
New. Print on demand Trade paperback (US). Glued binding. 340 p. Contains: Illustrations, black & white, Illustrations, color, Tables, black & white. Lecture Notes in Computational Science and Engineering, 58.
Add this copy of Principal Manifolds for Data Visualization and to cart. $252.18, good condition, Sold by BooksRun rated 4.0 out of 5 stars, ships from Philadelphia, PA, UNITED STATES, published 2007 by Springer.
Choose your shipping method in Checkout. Costs may vary based on destination.
Seller's Description:
Good. It's a well-cared-for item that has seen limited use. The item may show minor signs of wear. All the text is legible, with all pages included. It may have slight markings and/or highlighting.
