This article provides a new way for classifying heart disease. A classifier using a controller for brain emotional learning and a fuzzy system is presented. The controller's parameter updating laws are built using the gradient descent method. The method's convergence and stability are ensured by the Lyapunov function. Using the heart disease dataset from the University of California, Irvine (UCI), the performance of the system is examined. In addition, a comparison with different classifiers is provided. The outcomes of our experiments illustrate the efficacy of our strategy.
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