Classification biplot method

This function produces a list of elements to be used for constructing a classification biplot.

classification(bp, Pmat, dim.biplot = c(2, 1, 3), e.vects = 1:ncol(bp$X),
group.aes=NULL, axes = "regression", col=ez.col, opacity=0.4, borders = FALSE)

Arguments

bp

an object of class biplot obtained from preceding function biplot().

Pmat

a matrix containing the posterior probability for the classes

dim.biplot

dimension of the biplot. Only values 1, 2 and 3 are accepted, with default 2.

e.vects

which eigenvectors (principal components) to extract, with default 1:dim.biplot.

group.aes

vector of the same length as the number of rows in the data matrix for differentiated aesthetics for samples.

axes

type of axes, defaults to "regression"

col

colour of the classification regions

opacity

opacity of classification regions

borders

logical, indicating whether borders should be added to classification regions

Value

Object of class biplot with the following elements:

References

Gardner-Lubbe, S., 2016. A triplot for multiclass classification visualisation. Computational Statistics & Data Analysis, 94, pp.20-32.

Examples

biplot(iris[,1:4]) |> 
classification(predict(MASS::lda(Species ~ ., data = iris))$posterior)
#> Object of class biplot, based on 150 samples and 4 variables.
#> 4 numeric variables.
# create a classification biplot
biplot(iris[,1:4]) |> 
classification(predict(MASS::lda(Species ~ ., data = iris))$posterior) |> 
plot()
#> Warning: no non-missing arguments to min; returning Inf