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Minority report in fraud detection
2004
SIGKDD Explorations
This paper proposes an innovative fraud detection method, built upon existing fraud detection research and Minority Report, to deal with the data mining problem of skewed data distributions. This method uses backpropagation (BP), together with naive Bayesian (NB) and C4.5 algorithms, on data partitions derived from minority oversampling with replacement. Its originality lies in the use of a single meta-classifier (stacking) to choose the best base classifiers, and then combine these base
doi:10.1145/1007730.1007738
fatcat:z5sphecnpnbptbsrhr3fyzpq5i