principal component analysis
1principal component analysis — ( PCA) A mathematical tool used to reduce the number of variables while retaining the original variability of the data The first principal component accounts for as much of the variability in the data as possible, and each succeeding component… …
2Principal component analysis — PCA of a multivariate Gaussian distribution centered at (1,3) with a standard deviation of 3 in roughly the (0.878, 0.478) direction and of 1 in the orthogonal direction. The vectors shown are the eigenvectors of the covariance matrix scaled by… …
3Principal Component Analysis — Hauptkomponentenanalyse als Faktorenanalyse: Zwei Hauptkomponenten einer zweidimensionalen Punktwolke (orthogonal rotiert) Die Hauptkomponentenanalyse (englisch: Principal Component Analysis, PCA) ist ein Verfahren der multivariaten Statistik.… …
4Multilinear principal-component analysis — (MPCA) [1] is a mathematical procedure that uses multiple orthogonal transformations to convert a set of multidimensional objects into another set of multidimensional objects of lower dimensions. There is one orthogonal transformation for each… …
5Kernel principal component analysis — (kernel PCA) is an extension of principal component analysis (PCA) using techniques of kernel methods. Using a kernel, the originally linear operations of PCA are done in a reproducing kernel Hilbert space with a non linear mapping.ExampleThe two …
6Principal components analysis — Principal component analysis (PCA) is a vector space transform often used to reduce multidimensional data sets to lower dimensions for analysis. Depending on the field of application, it is also named the discrete Karhunen Loève transform (KLT),… …
7Principal geodesic analysis — In geometric data analysis and statistical shape analysis, principal geodesic analysis is a generalization of principal component analysis to a non Euclidean, non linear setting of manifolds suitable for use with shape descriptors such as medial… …
8Component analysis — may refer to: Principal component analysis Kernel principal component analysis Independent component analysis Neighbourhood components analysis ANOVA simultaneous component analysis Connected Component Analysis This disambiguation pag …
9Principal component regression — In statistics, principal component regression (PCR) is a regression analysis that uses principal component analysis when estimating regression coefficients.In PCR instead of regressing the independent variables (the regressors) on the dependent… …
10Independent component analysis — (ICA) is a computational method for separating a multivariate signal into additive subcomponents supposing the mutual statistical independence of the non Gaussian source signals. It is a special case of blind source separation. Definition When… …
