Tom E. Fawcett and Foster Provost Adaptive Fraud Detection Data Mining and Knowledge Discovery, 3(1):291--316, 1997.  Home/Search   Document Not in Database   Summary   Related Articles

....performance attainable by standard learning methods which assume a balanced distribution of the classes. For example, the problem occurs and hinders classification in applications as diverse as the detection of oil spills in satellite radar images [5] the detection of fraudulent telephone calls [1] and in flight helicopter gearbox fault monitoring [2] To this point, there have only been a few attempts at dealing with the class imbalance problem ( 7] 2] 6] 4] 1] 5] and these attempts were mostly conducted in isolation. In particular, there has not been, to date, any systematic ....

.... as diverse as the detection of oil spills in satellite radar images [5] the detection of fraudulent telephone calls [1] and in flight helicopter gearbox fault monitoring [2] To this point, there have only been a few attempts at dealing with the class imbalance problem ( 7] 2] 6] 4] [1], 5] and these attempts were mostly conducted in isolation. In particular, there has not been, to date, any systematic strive to link specific types of imbalances to the degree of inadequacy of standard classifiers. Furthermore, no comparison of the various methods proposed to remedy the ....

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Tom E. Fawcett and Foster Provost Adaptive Fraud Detection Data Mining and Knowledge Discovery, 3(1):291--316, 1997.

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