Publication | Closed Access
Uniqueness of the SVM Solution
95
Citations
9
References
1999
Year
Unknown Venue
Mathematical ProgrammingEngineeringMachine LearningSupport Vector SolutionSupport Vector MachineImage AnalysisData SciencePattern RecognitionSupervised LearningRegression EstimationInverse ProblemsComputer ScienceThreshold BSvm SolutionStatistical Learning TheorySparse RepresentationReproducing Kernel MethodStatistical InferenceKernel Method
We give necessary and sufficient conditions for uniqueness of the support vector solution for the problems of pattern recognition and regression estimation, for a general class of cost functions. We show that if the solution is not unique, all support vectors are necessarily at bound, and we give some simple examples of non-unique solutions. We note that uniqueness of the primal (dual) solution does not necessarily imply uniqueness of the dual (primal) solution. We show how to compute the threshold b when the solution is unique, but when all support vectors are at bound, in which case the usual method for determining b does not work.
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