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Unformatted text preview: 2   2 Margin w = ≤ + •≥ + • = 1 b x w if 1 1 b x w if 1 ) ( i i i x f 2   ) ( 2 w w L = Support Vector Machines • What if the problem is not linearly separable? Support Vector Machines • What if the problem is not linearly separable? – Introduce slack variables • Need to minimize: • Subject to: +≤ + •≥ + • = i i i i 1 b x w if 11 b x w if 1 ) ( ξ i x f + = ∑ = N i k i C w w L 1 2 2   ) ( Nonlinear Support Vector Machines • What if decision boundary is not linear? Nonlinear Support Vector Machines • Transform data into higher dimensional space...
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 Fall '09
 Data Mining, Optimization, Support vector machine, Constraint satisfaction, Vector Machines, Support Vector Machines

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