Classification biplot method — classification • biplotEZ

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

Usage

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()