I've made a series of predictions with a machine learning model. I have a list y
of labels and a list p
of predicted probabilities such that p[i]
is the predicted probability of the entry associated with y[i]
.
With Python's sklearn
library I ran
fprs, tprs, thresholds = metrics.roc_curve(y, p)
thresholds
is a list in descending order of decision thresholds, while fprs
and tprs
is the list of associated false positive rates and true positive rates where fprs[i]
and tprs[i]
are the respective rates given the decision threshold at thresholds[i]
.
My question is, given that thresholds
is in descending order, will fprs
and tprs
be guaranteed to be in ascending order? I believe that as the decision threshold decreases, more and more probabilities will be marked positive, thus both rates will increase monotonically.
But I've been wrong before about things that seem obvious to me, and I'm writing a tool that must assume these lists will be sorted in ascending order, so I'd like to be sure