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Nonexclusive classification characterizes many real problems in which a hard decision about data labels cannot be taken. In these cases, a decision system capable of fuzzy outputs is desirable, in order to well describe problem's nature and domain. In this paper, an algorithm pursuing this approach is presented. More precisely, a nonexclusive k-class problem is solved by the co-operation of k independent...
The use of clustering systems is very important in those real-word applications where an efficient, both accurate and economical, representation of the data to be processed is necessary. When dealing with statistical models, such a problem is usually related to the estimate of their parameters in the Maximum Likelihood context. At this regard, we propose an EM-based algorithm that uses a hierarchical...
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