Preprocessing the data — aux.preprocess • Rdimtools

aux.preprocess can perform one of following operations; "center", "scale", "cscale", "decorrelate" and "whiten". See below for more details.

aux.preprocess(
  data,
  type = c("center", "scale", "cscale", "decorrelate", "whiten")
)

Arguments

data: an \((n\times p)\) matrix or data frame whose rows are observations and columns represent independent variables.
type: one of "center", "scale", "cscale", "decorrelate" or "whiten".

Value

named list containing:

pX

an \((n\times p)\) matrix after preprocessing in accordance with type parameter

info

a list containing

type: name of preprocessing procedure.
mean: a mean vector of length \(p\).
multiplier: a \((p\times p)\) matrix or 1 for "center".

Operations

we have following operations,

"center": subtracts mean of each column so that every variable has mean \(0\).
"scale": turns each column corresponding to variable have variance \(1\).
"cscale": combines "center" and "scale".
"decorrelate": "center" and sets its covariance term having diagonal entries only.
"whiten": "decorrelate" and sets all diagonal elements be \(1\).

Author

Kisung You

Examples

# \donttest{
## Generate data
set.seed(100)
X = aux.gensamples(n=200)

## 5 types of preprocessing
X_center = aux.preprocess(X)
X_scale  = aux.preprocess(X,type="scale")
X_cscale = aux.preprocess(X,type="cscale")
X_decorr = aux.preprocess(X,type="decorrelate")
X_whiten = aux.preprocess(X,type="whiten")
# }