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We briefly describe our approach for the KDD99 Classification Cup. The solution is essentially a mixture of bagging and boosting. Additionally, asymmetric error costs are taken into account by minimizing the so-called conditional risk . Furthermore, the standard sampling with replacement methodology of bagging was modified to put a specific focus on the smaller but expensive-if-predicted-wrongly classes.
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Bernhard Pfahringer (2000) studied this question.
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