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The positive class in a binary classification problem, is usually the class of interest (e.g: fraud, spam, cancer).

Machine learning algorithms try to construct a classifier that can separate these two classes. Here, it does not matter what you call "positive" or "1" or "true"...


Are there examples for problems/algorithms where it is important to define something like a class of interest in supervised learning?

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