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The belief rules which extend the classical fuzzy IF-THEN rules with belief consequent parts have been widely used for classifier design due to their capabilities of building linguistic models interpretable to users and addressing various types ...

• Fuzzy belief decision tree is designed to generate compact and accurate belief rule base.
• A fuzzy information gain ratio is defined as the feature selection criterion for node splitting.
• Belief distribution is introduced to each ...

In hybrid classification problems, apart from labeled data, some related expert knowledge may also be obtained. If the partial information from these two sources can be jointly used well, the performance may be effectively improved. To this end, ...

As one of the most promising classification approaches, association classification (AC) integrates data classification and association discovery techniques for generating a compact set of classification association rules. Recently, the fuzzy set ...

In multiple attribute decision analysis (MADA) problems, one often needs to deal with assessment information with uncertainty. The evidential reasoning approach is one of the most effective methods to deal with such MADA problems. As a kernel of the ...