Adaptive fraud detection. Data Mining and Knowledge Discovery (1997)

Cached

Download Links

by Tom Fawcett , Foster Provost
Citations:63 - 3 self

Active Bibliography

164 Adaptive Fraud Detection – Tom Fawcett, Foster, Foster Provost - 1997
14 Distributed Data Mining: Scaling up and beyond – Foster Provost - 1999
46 Combining Data Mining and Machine Learning for Effective User Profiling – Tom Fawcett, Foster Provost - 1996
7 Rule-Space Search for Knowledge-Based Discovery – Foster Provost, John M. Aronis, Bruce G. Buchanan - 1999
53 Scaling Up: Distributed Machine Learning with Cooperation – Foster John Provost, Daniel N. Hennessy - 1996
19 The WoRLD: Knowledge Discovery from Multiple Distributed Databases – John M. Aronis, Venkateswarlu Kolluri, Foster J. Provost, Bruce G. Buchanan - 1997
18 A Survey of Methods for Scaling Up Inductive Learning Algorithms – Foster J. Provost, Venkateswarlu Kolluri - 1997
15 Increasing the Efficiency of Data Mining Algorithms with Breadth-First Marker Propagation – John M. Aronis, Foster J. Provost - 1997
64 Statistical Fraud Detection: A Review – Richard J. Bolton, David J. Hand, David J. H - 2002
2 Machine Learning as Massive Search – Richard B. Segal - 1997
135 Separate-and-conquer rule learning – Johannes F├╝rnkranz - 1999
85 A Survey of Methods for Scaling Up Inductive Algorithms – Foster Provost, Venkateswarlu Kolluri - 1999
36 Using Rule Sets to Maximize ROC Performance – Tom Fawcett - 2001
4 Beyond Association Rules: Generalized Rule Discovery – Geoffrey I. Webb, Songmao Zhang
35 On Detecting Differences Between Groups – Geoffrey I. Webb, Shane M. Butler, Douglas Newlands - 2003
1 Further Pruning for Efficient Association Rule Discovery – Songmao Zhang, Geoffrey I. Webb
42 Inductive Policy: The Pragmatics of Bias Selection – Foster John Provost, Bruce G. Buchanan - 1995
59 Efficient Search for Association Rules – Geoffrey I. Webb - 2000
2 Use of Domain Knowledge in Constructive Induction – James P. Callan - 1990