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The Impact of Overfitting and Overgeneralization on the Classification Accuracy in Data Mining
[chapter]
2008
Soft Computing for Knowledge Discovery and Data Mining
Many classification studies often times conclude with a summary table which presents performance results of applying various data mining approaches on different datasets. No single method outperforms all methods all the time. Furthermore, the performance of a classification method in terms of its false-positive and false-negative rates may be totally unpredictable. Attempts to minimize any of the previous two rates, may lead to an increase on the other rate. If the model allows for new data to
doi:10.1007/978-0-387-69935-6_16
dblp:series/springer/PhamT08
fatcat:nahnhiqlwvhcbeoncqwob5ma7q