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Erschienen in:
2010 | OriginalPaper | Buchkapitel
The Reliability Issue in Data Mining: The Case of Computer-Aided Breast Cancer Diagnosis
verfasst von : Evangelos Triantaphyllou
Erschienen in: Data Mining and Knowledge Discovery via Logic-Based Methods
Verlag: Springer US
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Almost any use of a data mining and
sub data mining
sub knowledge discovery, see
data mining
knowledge discovery method on a data set requires some discussion on the accuracy of the extracted model on some test data. This accuracy can be a general description of how well the extracted model classifies test data. Some studies split this
sub accuracy rate
accuracy rate into two rates: the
sub false-positive
false-positive and
sub false-negative
false-negative rates. This distinction might be more appropriate for most real-life applications. For instance, it is one thing to wrongly diagnose a benign tumor as malignant than the other way around. Related are some of the discussions in Sections 1.3.4, 4.5, and 11.6.