Rule extraction using ensemble of neural network ensembles

Neural networks are well-known for their impressive classification performance, and the ensemble learning technique acts as a catalyst to improve this performance even further by integrating multiple networks. However, neural network ensembles, like networks, regarded black box because they cannot explain decision-making process. As result, despite high ensembles unsuitable some applications that require explainable decisions. rule extraction can overcome drawback representing knowledge learned in guise of interpretable decision rules. A algorithm provides ability justify responses using There several algorithms extracting rules from but only few them use generate paper proposes called Rule Extraction Using Ensemble Network Ensembles (RE-E-NNES) demonstrate ensembles. RE-E-NNES extracts ensembling The results efficacy proposed comparison other existing algorithms.