Support-Vector Networks C Cortes and V Vapnik 12.04.26.(Tue) Computational Models of Intelligence Joon Shik Kim.

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Presentation transcript:

Support-Vector Networks C Cortes and V Vapnik (Tue) Computational Models of Intelligence Joon Shik Kim

Introduction The support-vector network is a new learning machine for two-group classification problems. Input vectors are non-linearly mapped to a very high dimension feature space. In this feature space a linear decision surface is constructed.

Graphical Description of SVM

Optimal Hyperplane Algorithm (1/2) The set of labeled training patterns is said to be linearly separable if there exists a vector w and a scalar b such that the inequalities if

Optimal Hyperplane Algorithm (2/2) The optimal hyperplane Distance is given by

Lagrangian (1/2)

Lagrangian (2/2)