Abstract
In this article, we propose a reformulation of ε-insensitive Support Vector Regression as a classification problem with a priori knowledge in the form of detractors. So we can use the one general solver for Support Vector Machines classification and regression problems. Moreover, we can apply all the applications for a priori knowledge in the form of detractors also for ε-insensitive Support Vector Regression. These are manipulating of the regression function and creating improved reduced models by removing support vectors. Indeed, the experiments show that the new reformulation of Support Vector Regression leads to an effective application of detractors for regression problems. The tests were performed on various regression data sets and on stock price data from public domain repositories.KeywordsSupport Vector Machinesa priori knowledge
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