 | Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data... 113 KB (14,220 words) - 20:36, 16 April 2024 |
multivariate statistics, kernel principal component analysis (kernel PCA) is an extension of principal component analysis (PCA) using techniques of kernel... 9 KB (1,275 words) - 04:44, 25 July 2023 |
Functional principal component analysis (FPCA) is a statistical method for investigating the dominant modes of variation of functional data. Using this... 14 KB (1,888 words) - 13:45, 3 February 2024 |
Robust Principal Component Analysis (RPCA) is a modification of the widely used statistical procedure of principal component analysis (PCA) which works... 14 KB (1,724 words) - 18:51, 5 February 2024 |
Multilinear principal component analysis (MPCA) is a multilinear extension of principal component analysis (PCA) that is used to analyze M-way arrays,... 9 KB (990 words) - 02:13, 10 March 2024 |
In statistics, principal component regression (PCR) is a regression analysis technique that is based on principal component analysis (PCA). More specifically... 33 KB (4,836 words) - 00:00, 3 January 2024 |
Component analysis may refer to one of several topics in statistics: Principal component analysis, a technique that converts a set of observations of... 1 KB (171 words) - 15:42, 29 December 2020 |
(2009). "Principal component analysis vs. exploratory factor analysis" (PDF). SUGI 30 Proceedings. Retrieved 5 April 2012. SAS Statistics. "Principal Components... 72 KB (9,799 words) - 19:36, 29 March 2024 |
 | principal component analysis (L1-PCA) is a general method for multivariate data analysis. L1-PCA is often preferred over standard L2-norm principal component... 19 KB (2,279 words) - 02:02, 27 August 2023 |
In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents.... 43 KB (6,418 words) - 23:37, 15 March 2024 |