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Principal Manifolds for Data Visualization and Dimension Reduction
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Principal Manifolds for Data Visualization and Dimension Reduction

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.

Upplaga
2008 ed.
ISBN
9783540737490
Språk
Engelska
Vikt
310 gram
Utgivningsdatum
2007-10-01
Sidor
340