Naive possibilistic classifiers for imprecise or uncertain numerical data
نویسندگان
چکیده
منابع مشابه
Naive possibilistic classifiers for imprecise or uncertain numerical data
In real-world problems, input data may be pervaded with uncertainty. In this paper, we investigate the behavior of naive possibilistic classifiers, as a counterpart to naive Bayesian ones, for dealing with classification tasks in presence of uncertainty. For this purpose, we extend possibilistic classifiers, which have been recently adapted to numerical data, in order to cope with uncertainty i...
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ژورنال
عنوان ژورنال: Fuzzy Sets and Systems
سال: 2014
ISSN: 0165-0114
DOI: 10.1016/j.fss.2013.07.012