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One-class classification, also known as unary classification, tries to identify objects of a specific class amongst all objects, by learning from a training set containing only the objects of that class. This is different from and more difficult than the traditional classification problem, which tries to distinguish between two or more classes with the training set containing objects from all the classes. PU (positive unlabelled) learning is a special case

3 votes

Metrics for one-class classification

Though it's a late reply, I'd like to point of implicit assumptions by previous answers that likely don't hold. for one-class classification, we don't know the real ratio of positive and negative da …
yiping's user avatar
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