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• W2183699034 abstract "A fuzzy prototype-based method is introduced for learning from examples. A special kind of prototype vector with fuzzy attributes is derived for each class from aggregating fuzzified cases for the purpose of concept description. The fuzzified cases are derived by defining a fuzzy membership function for each attribute of the sample cases. In a first method, for the classification of a new case, the membership degrees of its crisp attributes to fuzzy aggregated prototypes are measured. In a second method, after fuzzifying the new case, fuzzy set comparison methods are applied for measuring the similarity. The methods are compared to case-based ones like POSSIBL and kNN using UCI machine learning repository. We also make comparisons by using various transformation methods from probabilities to possibilities instead of defining membership functions." @default.
• W2183699034 created "2016-06-24" @default.
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• W2183699034 date "2008-01-01" @default.
• W2183699034 modified "2023-09-27" @default.
• W2183699034 title "Prototype-based classification by fuzzification of cases" @default.
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