In particular, principal components regression selects factors that explain as much predictor variation as possible, reduced rank regression selects factors that explain as much response variation as ...

The principal components are sorted by descending order of their variances, which are equal to the associated eigenvalues. Principal components can be used to reduce the number of variables in ...

Researchers at University of Tsukuba have applied a visualization technique to depict the brain's activity related to visual perception as geometric patterns. They visualized different shapes as the ...

Principal component analysis (PCA) is a mathematical algorithm that reduces the dimensionality of the data while retaining most of the variation in the data set 1. It accomplishes this reduction ...