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Construct a Discriminant Projector

discriminant_projector.Rd

A discriminant_projector is an instance that extends bi_projector with a projection that maximizes class separation. This can be useful for dimensionality reduction techniques that take class labels into account, such as Linear Discriminant Analysis (LDA).

Usage

discriminant_projector(
  v,
  s,
  sdev,
  preproc = prep(pass()),
  labels,
  classes = NULL,
  ...
)

Arguments

v

The projection matrix (often X %*% v). Rows correspond to observations, columns to components.

s

The score matrix (often X %*% v). Rows correspond to observations, columns to components.

sdev

The standard deviations associated with the scores or components (e.g., singular values from LDA).

preproc

A prepper or pre_processor object, or a pre-processing function (e.g., center, pass).

labels

A factor or character vector of class labels corresponding to the rows of X (and s).

classes

Additional S3 classes to prepend.

...

Extra arguments passed to bi_projector.

Value

A discriminant_projector object.

See also

bi_projector

Examples

# Simulate data and labels
set.seed(123)
X <- matrix(rnorm(100 * 10), 100, 10)
labels <- factor(rep(1:2, each = 50))

# Perform LDA and create a discriminant projector
lda_fit <- MASS::lda(X, labels)

dp <- discriminant_projector(lda_fit$scaling, X %*% lda_fit$scaling, sdev = lda_fit$svd, 
labels = labels)