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Erschienen in:
2010 | OriginalPaper | Buchkapitel
A Fuzzy Logic Approach to Attribute Formalization: Analysis of Lobulation for 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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In many data mining and
sub data mining
sub knowledge discovery, see
data mining
knowledge discovery applications a critical task is how to define the values of the various attributes that the analyst believes may be of significance. For easily quantifiable attributes (such as, age, weight, cost, etc.) this task is a rather straightforward one as it involves simple measurements and expressing the results in terms of some units. For other attributes, however, this task may not be a simple one. This is the case when some of the data are
fuzzy
. For instance, although in common language one often uses terms such as “small,” “large,” “round,” “tall,” and so on, these terms may mean different concepts to different people or to the same person at different times.