
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
