9 citations · 9 across the 1 of their papers we have counts for
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cs.AI2018
Machine learning 2.0 : Engineering Data Driven AI Products
James Max Kanter, Benjamin Schreck, Kalyan Veeramachaneni
ML 2.0: In this paper, we propose a paradigm shift from the current practice of creating machine learning models - which requires months-long discovery, exploration and "feasibilit…
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…