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Erschienen in:
1999 | OriginalPaper | Buchkapitel
Classifier Design
verfasst von : James C. Bezdek, James Keller, Raghu Krisnapuram, Nikhil R. Pal
Erschienen in: Fuzzy Models and Algorithms for Pattern Recognition and Image Processing
Verlag: Springer US
Enthalten in: Professional Book Archive
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In Section 1.1 we defined a classifier as any function D:ℜp ↦ Npc. The value y = D(z) is the label vector for z in ℜP. D is a crisp classifier if D [ℜp] = Nhc; otherwise, the classifier is fuzzy, possibilistic or probabilistic, which for convenience we lump together as soft classifiers. This chapter describes some of the most basic (and often most useful) classifier designs, along with some fuzzy generalizations and relatives.