Classification problems are significant because they constitute a meta-model for multiple theoretical and practical applications from a wide range of fields. The belief rule based (BRB) expert system has shown potentials in dealing with both quantitative and qualitative information under uncertainty. In this study, a BRB classifier is proposed to solve the classification problem. However, two challenges must be addressed. First, the size of the BRB classifier must be controlled within a feasible
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