rtemis (version 0.79)

d.PCA: Principal Component Analysis

Description

Perform PCA decomposition using stats::prcomp

Usage

d.PCA(x, x.test = NULL, k = NULL, scale = TRUE, center = TRUE,
  verbose = TRUE, ...)

Arguments

x

Input matrix

x.test

Optional test set. Will be projected on to PCA basis

k

Integer: Number of right singular vectors to compute (svd's nv)

scale

Logical: If TRUE, scale input data before doing SVD

center

Logical: If TRUE, also center input data if scale is TRUE

verbose

Logical: If TRUE, print messages to screen. Default = TRUE

...

Additional parameters to be passed to PCA::PCA

Value

rtDecom object

Details

Same solution as d.SVD. d.PCA runs prcomp, which has useful summary output

See Also

Other Decomposition: d.CUR, d.H2OAE, d.H2OGLRM, d.ICA, d.ISOMAP, d.KPCA, d.LLE, d.MDS, d.NMF, d.SPCA, d.SVD, d.TSNE, d.UMAP