discriminant_projector {multivarious} | R Documentation |
Construct a Discriminant Projector
Description
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 |
A matrix of coefficients with dimensions |
s |
The score matrix |
sdev |
The standard deviations of the score matrix |
preproc |
(optional) A pre-processing pipeline, default is prep(pass()) |
labels |
A factor or character vector of class labels corresponding to the rows of the score matrix |
classes |
(optional) A character vector specifying the class attributes of the object, default is NULL |
... |
Extra arguments to be stored in the |
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)