Support Vector Machine (SVM) is a new and very promising classification technique. The approach is systematic and properly motivated by statistical learning theory. Training invovles separating the classes with a surface that maximizes the margin between them. An interesting property of this approach is that it is an approximate implementation of the Structural Risk Minimizaiton (SRM) induction principle.
In this thesis, the theory and method of Support Vector Machines wer...
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