I have a multinomial model constructed with nnet:multinom
of 5 classes for 26 variables:
mirna_multinom_0 = multinom(formula_0, data= clase_training, maxit=10000 )
And then I create my ROCS with:
multiclass.roc(clase_training$clase, mirna_multinom_0$fitted.values,plot=TRUE)
Which I plot.
pred_test_inter_multinom_5 = predict(interaction_multinom_model_5, newdata = clase_test, "probs")
multiclass.roc(clase_test$clase, pred_test_inter_multinom_5,plot=TRUE)
To understand them I store it as an object e
and call the contrast as names(e$roc)
to see my contrasts.
e = multiclass.roc(clase_training$clase, mirna_multinom_0$fitted.values)
names(e$rocs)
[1] "Control/Idiop_grave" "Control/Idiop_leve" "Control/Isquem_grave"
[4] "Control/Isquem_leve" "Idiop_grave/Idiop_leve" "Idiop_grave/Isquem_grave"
[7] "Idiop_grave/Isquem_leve" "Idiop_leve/Isquem_grave" "Idiop_leve/Isquem_leve"
[10] "Isquem_grave/Isquem_leve"
Which gives me 2 plots for each of them, 1 in > direction and the other in < direction.
Now. Can I plot the titles of each contrast in the plots in someway?
And also, is there a way I can obtain the areas under the curve AUC for each one of the ROC contrast? I only obtain it in a message for the multinomial. Which don't have a PROC plot. Can I obtain a multinomial ROC, or its just a construct with no graphical representation?
Can I plot the titles of each contrast in the plots in someway?
You will need to loop over the curves yourself, but it can be done easily like:
for (contrast in names(e$rocs)) {
plot(e$rocs[[contrast]][[1]], col = "green", main = contrast)
plot(e$rocs[[contrast]][[2]], col = "blue", add = TRUE)
}
is there a way I can obtain the areas under the curve AUC for each one of the ROC contrast?
You can do something similar with the auc
function:
for (contrast in names(e$rocs)) {
print(contrast)
print(auc(e$rocs[[contrast]][[1]]))
print(auc(e$rocs[[contrast]][[2]]))
}
Can I obtain a multinomial ROC, or its just a construct with no graphical representation?
It is a sort of average of AUC described by Hand & Till in doi:10.1023/A:1010920819831. There is no corresponding curve to be represented.