3Principal Components Analysis: A Brief Visit
Centering and Scaling: An Example
The Importance of Exploratory Data Analysis in Multivariate Studies
Dimensionality Reduction via PCA
Principal Components Analysis
Like PLS, principal components analysis (PCA) attempts to use a relatively small number of components to model the information in a set of data that consists of many variables. Its goal is to describe the internal structure of the data by modeling its variance. It differs from PLS in that it does not interpret variables as inputs or outputs, but rather deals only with a single matrix. The single matrix is usually denoted by X. Although the components that are extracted can be used in predictive models, in ...
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