Component analysis information

Principal component analysis (PCA) is a linear dimensionality reduction technique with applications in exploratory data analysis, visualization and data...

In signal processing, independent component analysis (ICA) is a computational method for separating a multivariate signal into additive subcomponents....

Component analysis may refer to one of several topics in statistics: Principal component analysis, a technique that converts a set of observations of...

Componential analysis (feature analysis or contrast analysis) is the analysis of words through structured sets of semantic features, which are given as...

multivariate statistics, kernel principal component analysis (kernel PCA) is an extension of principal component analysis (PCA) using techniques of kernel methods...

Functional principal component analysis (FPCA) is a statistical method for investigating the dominant modes of variation of functional data. Using this...

Robust Principal Component Analysis (RPCA) is a modification of the widely used statistical procedure of principal component analysis (PCA) which works...

the components of a particular chemical compound (qualitative analysis), to identify the proportions of components in a mixture (quantitative analysis),...

Formal concept analysis Independent component analysis Non-negative matrix factorization Q methodology Recommendation system Root cause analysis Facet theory...

smaller components. This analysis is generally is based on graphical forms, without considering aspects like pronunciation and meaning. Component analysis is...

considered at a particular level of analysis Lumped element model, a model of spatially distributed systems Component video, a type of analog video information...

Multilinear principal component analysis (MPCA) is a multilinear extension of principal component analysis (PCA) that is used to analyze M-way arrays,...

counterpart of principal component analysis for categorical data. MCA can be viewed as an extension of simple correspondence analysis (CA) in that it is applicable...

dimensions. The data transformation may be linear, as in principal component analysis (PCA), but many nonlinear dimensionality reduction techniques also...

Dependent component analysis (DCA) is a blind signal separation (BSS) method and an extension of Independent component analysis (ICA). ICA is the separating...

LDA method. LDA is also closely related to principal component analysis (PCA) and factor analysis in that they both look for linear combinations of variables...

correspond to principal components and the eigenvalues to the variance explained by the principal components. Principal component analysis of the correlation...

dimensionality reduction, such as singular value decomposition and principal component analysis. Consider a dataset represented as a matrix (or a database table)...

principal component analysis (PCA), independent component analysis (ICA), linear discriminant analysis (LDA) and canonical correlation analysis (CCA). Multilinear...

Directional component analysis (DCA) is a statistical method used in climate science for identifying representative patterns of variability in space-time...

Neighbourhood components analysis is a supervised learning method for classifying multivariate data into distinct classes according to a given distance...

principal component analysis, but applies to categorical rather than continuous data. In a similar manner to principal component analysis, it provides...

and data dissemination. Analysis refers to dividing a whole into its separate components for individual examination. Data analysis is a process for obtaining...

ANCOVA – redirects to Analysis of covariance Anderson–Darling test ANOVA ANOVA on ranks ANOVA–simultaneous component analysis Anomaly detection Anomaly...