Shows a plot with discrimination power of predictors for a pair of SIMCA models
# S3 method for simcam
plotDiscriminationPower(
obj,
nc = c(1, 2),
type = "h",
main = paste0("Discrimination power: ", obj$classnames[nc[1]], " vs. ",
obj$classname[nc[2]]),
xlab = attr(obj$dispower, "xaxis.name"),
ylab = "",
...
)
a SIMCAM model (object of class simcam
)
vector with two values - classes (SIMCA models) to show the plot for
type of the plot
main plot title
label for x axis
label for y axis
other plot parameters (see mdaplotg
for details)
Discrimination power shows an ability of variables to separate classes. The power is computed similar to model distance, using variance of residuals. However in this case instead of sum the variance across all variables, we take the ratio separately for individual variables.
Discrimination power equal or above 3 is considered as high.