The symbolic approach to machine learning has developed algorithms for learning first-order logic concept definitions. Nevertheless, most of them are limited because of their inability to cope with numeric features, typical of real-world data. A method to overcome this problem is proposed called fuzzy concept. It is understood by scientists as a concept which is “to an extent applicable” in a situation, and it therefore implies gradations of meaning.
Fuzzy Concept
