Rule Extraction from Support Vector Machine

Although Support Vector Machines have been used to develop highly accurate classification and regression models in various real-world problem domains, the most significant barrier is that SVM generates black box model that is difficult to understand. The procedure to convert these opaque models into transparent models is called rule extraction. This thesis investigates the task of extracting compr...