Produces two plots for model evaluation. The first plot shows the Receiver Operating Characteristic (ROC)-curves, the other the Precision-recall (PR)-curves for the different cross-validation repetitions.
model.evaluation.plot(..., fn.plot = NULL, colours=NULL, show.all=FALSE, verbose = 1)
one or more object of class siamcat-class, can be named
string, filename for the pdf-plot
colour specification for the different siamcat-class-
objects, defaults to
boolean, Should all repeated cross-validation models be plotted?
Does not return anything, but produces the model evaluation plot.
data(siamcat_example) # simple working example model.evaluation.plot(siamcat_example, fn.plot='./eval.pdf') #> Plotted evaluation of predictions successfully to: ./eval.pdf # plot several named SIAMCAT object # (although we use only one example object here) model.evaluation.plot('Example_1'=siamcat_example, 'Example_2'=siamcat_example, colours=c('red', 'blue'), fn.plot='./eval.pdf') #> Plotted evaluation of predictions successfully to: ./eval.pdf