13. In NLP and ML, we often have the case where we are trying tofind a relatively-speaking small number of target concepts in avast sea of noise? For example, in a given domino game playingimage there are 28 or fewer dominos in the image out of a vastnumber of possible image segments. In classifying blood samples asindicating a particular disease, maybe the odds of any given samplehaving the disease are 1 in a million. What is the typical metricdiscussed in class that we use in ML to evaluate a classifier inthis sort of scenario, where we have an imbalanced dataset
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