
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.
- Opplag
- 2008 ed.
- ISBN
- 9783540737490
- Språk
- Engelsk
- Vekt
- 310 gram
- Utgivelsesdato
- 1.10.2007
- Antall sider
- 340
