most citedSolving the "false positives" problem in fraud prediction

9 citations · 9 across the 1 of their papers we have counts for

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1 paper

cs.AI2017★ 9 cited

Solving the "false positives" problem in fraud prediction

Roy Wedge, James Max Kanter, Santiago Moral Rubio +2

In this paper, we present an automated feature engineering based approach to dramatically reduce false positives in fraud prediction. False positives plague the fraud prediction in…