PCA

Description

Principal component analysis (PCA) is a mathematical procedure that uses an orthogonal transformation to convert a set of observations of possibly correlated variables into a set of values of linearly uncorrelated variables called principal components. See PCA




Usage

Field Description
Launch Field indicating whether you want to execute this analysis in the workflow (checked) or not (unchecked).

to finish …



Output Examples