



Last update: February 19, 2014






Sensitivity
The sensitivity is widely used in medicine and consists of the probability of
a diagnostic test finding disease among those who have the disease or
the proportion of people with the disease who have a positive test result. More formally,
the sensitivity SE_{i} of an individual model
i is evaluated by the equation:
where TP_{i} and
FN_{i} represent, respectively, the number of
true
positives and false
negatives.
True positives (TP), true negatives (TN),
false positives (FP), and false negatives (FN), are the four
different possible outcomes of a single prediction for a
binomial classification task with classes “1” (“yes”) and “0” (“no”). A
false positive is when the outcome is incorrectly classified as “yes” (or “positive”),
when it is in fact “no” (or “negative”). A
false negative is when the outcome is incorrectly classified as negative when
it is in fact positive.
True positives and true negatives are obviously correct classifications.
These four types of classifications are usually shown in a twoway table called the
confusion matrix.
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