Controlling selectivity in nonstandard pattern recognition algorithms

A type of aggregation operator, referred to as mixed connectives, is used to summarize the information about objects to be classified (supplied by the descriptors). Because mixed connectives depend on a parameter, this leads to the concept of families for these operators. Therefore, given such a family, it is possible to associate different classifications with the same data set, depending on the value chosen for the parameter. The manner in which the algorithm selectivity classifications are compared is illustrated by an example involving a quantitative data basis.<
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