Ideas on this fraud detection problem

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I have ~6k positive samples of a fraud class; and ~110k unlabeled samples of mostly negative classes. Although I don't have labels for these 110k samples, I assume that the majority belongs to the negative class. However, in my assumption, I know that there are some positive samples in this unlabeled data set.

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