Abstract
We propose a new formulation for the optimal separation problems. This robust formulation is based on finding the minimum volume ellipsoid covering the points belong to the class. Idea is to separate by ellipsoids in the input space without mapping data to a high dimensional feature space unlike Support Vector Machines. Thus the distance order in the input space is preserved. Hopfield Neural Network is described for solving the optimization problem. The benchmark Iris data is given to evaluate the formulation.
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© 2006 Springer-Verlag Berlin Heidelberg
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Uçar, A., Demir, Y., Güzeliş, C. (2006). A New Formulation for Classification by Ellipsoids. In: Savacı, F.A. (eds) Artificial Intelligence and Neural Networks. TAINN 2005. Lecture Notes in Computer Science(), vol 3949. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11803089_12
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DOI: https://doi.org/10.1007/11803089_12
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-36713-0
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