Abstract
Classification is an important data mining task in biomedicine. For easy comprehensibility, rules are preferrable to another functions in the analysis of biomedical data. The aim of this work is to use a new fuzzy immune rule-based classification system for biomedical data. The performance of the proposed approach, in terms of classification accuracy and area under the ROC curve, was compared with traditional classifier schemes: C4.5, Naive Bayes, K*, and Meta END.
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