Sequential minimal optimization: Difference between revisions

Revision as of 16:20, 19 July 2013

Revision as of 09:33, 30 July 2013

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| last = Platt | first = John

| year = 1998

| title = [http://www.bradblock.com/Sequential_Minimal_Optimization_A_Fast_Algorithm_for_Training_Support_Vector_Machine.pdf Sequential Minimal Optimization: A Fast Algorithm for Training Support Vector Machines]

| id = {{citeseerx|10.1.1.43.4376}}

}}</ref> SMO is widely used for training support vector machines and is implemented by the popular [[LIBSVM]] tool.<ref>{{cite journal

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:<math>0 \leq \alpha_1, \alpha_2 \leq C,</math>

:<math>y_1 \alpha_1 + y_2 \alpha_2 = k,</math>

and this reduced problem can be solved analytically: one needs to find a minimum of a one-dimensional quadratic function. <math>k</math> is the sum over the rest of terms in the equality constraint, which is fixed in each iteration.

The algorithm proceeds as follows: