Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data...
114 KB (14,281 words) - 18:23, 16 May 2024
Functional principal component analysis (FPCA) is a statistical method for investigating the dominant modes of variation of functional data. Using this...
14 KB (1,986 words) - 13:45, 3 February 2024
multivariate statistics, kernel principal component analysis (kernel PCA) is an extension of principal component analysis (PCA) using techniques of kernel...
9 KB (1,334 words) - 07:13, 15 May 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
Robust Principal Component Analysis (RPCA) is a modification of the widely used statistical procedure of principal component analysis (PCA) which works...
15 KB (1,756 words) - 01:28, 3 May 2024
In statistics, principal component regression (PCR) is a regression analysis technique that is based on principal component analysis (PCA). More specifically...
33 KB (5,077 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 (10,026 words) - 02:37, 10 May 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...
18 KB (2,329 words) - 01:29, 9 May 2024
In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents....
43 KB (6,665 words) - 23:37, 15 March 2024