Eclectic Rule-Extraction from Support Vector Machines

  title={Eclectic Rule-Extraction from Support Vector Machines},
  author={Nahla H. Barakat and Joachim Diederich},
Support vector machines (SVMs) have shown superior performance compared to other machine learning techniques, especially in classification problems. Yet one limitation of SVMs is the lack of an explanation capability which is crucial in some applications, e.g. in the medical and security domains. In this paper, a novel approach for eclectic rule-extraction from support vector machines is presented. This approach utilizes the knowledge acquired by the SVM and represented in its support vectors… CONTINUE READING
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