Mohamed EL Boujnouni1, Mohamed Jedra2
Computer Systems Science and Engineering, Vol.33, No.6, pp. 409-420, 2018, DOI:10.32604/csse.2018.33.409
Abstract Support Vector Domain Description (SVDD) is an effective kernel-based method used for data description. It was motivated by the success of Support Vector
Machine (SVM) and thus has inherited many of its attractive properties. It has been extensively used for novelty detection and has been applied successfully
to a variety of classification problems. This classifier aims to find a sphere with minimal volume including the majority of examples that belong to the class
of interest (positive) and excluding the most of examples that are either outliers or belong to other classes (negatives). In this paper we propose a new
approach… More >
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