7-classification-SVM

234052 l let u b0 1 s i p s c bounds

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Unformatted text preview: coefs [,1] [1,] 1 ii [2,] -1 > x.svm$rho [1] -0.2410567 > wcoefs <- t(as.matrix(x.svm$coefs))%*%x.svm$SV > wcoefs x1 x2 [1,] 1.056296 0.879014 s=2 "y Statistics 503, Spring 2013, ISU 11 67-8#,$ > x.svm$SV x1 x2 81 0.5228230 0.2029103 127 -0.5334726 -0.6761037 > x.svm$coefs [,1] [1,] 1 ii [2,] -1 > x.svm$rho [1] -0.2410567 > wcoefs <- t(as.matrix(x.svm$coefs))%*%x.svm$SV > wcoefs x1 x2 [1,] 1.056296 0.879014 s=2 "y b Statistics 503, Spring 2013, ISU 11 67-8#,$ > x.svm$SV x1 x2 81 0.5228230 0.2029103 127 -0.5334726 -0.6761037 > x.svm$coefs [,1] [1,] 1 ii [2,] -1 > x.svm$rho 0 [1] -0.2410567 > wcoefs <- t(as.matrix(x.svm$coefs))%*%x.svm$SV > wcoefs x1 x2 [1,] 1.056296 0.879014 s=2 "y b b Statistics 503, Spring 2013, ISU 11 1 ||b||2 2 1./),%23'/$/40)#,%,52) ESS + λ ￿ 2 ωl l Let u = b0 + ￿ +./.<.>)' n ￿ ˆ 2/2ESS C Y '''''''''''''''''||b|| + = (#ii − Y )2 i=1 0":I)*&'&$'#i ! 0, yi ( xTb+b0) ! 1-#i bi X i 1 1 + e−u 2 1 √ e−u /2 2π {x : x￿ b + b = 0} ￿u ￿ 2 2/π s e−z /2 δ z ￿ 0 b= (αi · yi )xi Statistics 503, Spring 2013, ISU i=1 u e − e−u eu + e−u 1 ||b||2 2 p s ￿ ￿ ˆ Y = a0 + (aj (b￿ bij Xi )) 0j + 2 ESS + λ ωi=1 j =1 l 12 1./),%23'/$/40)#,%,52) l Let u = b0 + ￿ (1 − λ)S + λI, p s +./.<.>)' ￿ C￿ bounds the influence n ˆ = g (a0 + Y (￿ (b0j + 2 bij Xi ))) aj f = '''''''''''''''''||b||2/2ESS=1 (#ii − Yi) of these points +j C Y ˆ =1 i=1 0":I)*&'&$'#i ! 0, yi ( xTb+b0) ! 1-#i bi X i ˆ Y = f (a0 + 4 ￿ (aj f (b0j + b X ))) 1 ij i i=1 1 + e−u j =1 λ ∈ [0, 1] 2 ￿ f = logit function 2 1 √ e−u /2 π¯ ¯ (Xk − X0 )￿ S−1 2(Xk − X0 ) − logpk pooled ￿ 2/π ￿ 0 u −z 2 /2 1e δz Statistics 503, Spring 2013, ISU eu − e−u eu + e−u 12 1 ||b||2 2 1./),%23'/$/40)#,%,52) ESS + λ ￿ 2 ωl l Let u = b0 + ￿ +./.<.>)' C bounds the influence n ￿ '''''''''''''''''||b||2/2ESS C (#ii − Y )2 of these points += Y ˆ i=1 0":I)*&'&$'#i ! 0, yi (...
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This note was uploaded on 02/06/2014 for the course STAT 503 taught by Professor Staff during the Fall '08 term at Iowa State.

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