Logistic Regression, Prediction and ROC

70 71 search for optimal cut off probability the

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Unformatted text preview: double penalizing getting 1 wrong). https://blackboar d.uc.edu/bbcswebdav/pid- 9566224- dt- content- r id- 55868231_2/cour ses/14SS_BANA7046002/notes%284%29.html 10/15 2/17/2014 Log istic Reg r ession, Pr ediction and ROC pu =02 ct . #Smerccs ymti ot cs1< fnto(,p){ ot - ucinr i ma(( = 0 &(i>pu) |(r= 1 &(i< en(r = ) p ct) ( =) p pu)) ct) } #Aymti cs smerc ot cs2< fnto(,p){ ot - ucinr i wih1=2 egt wih0=1 egt c =( = 1 &(i<pu) #oia vco -tu i 1 r=) p ct lgcl etr re f ata 1btpeit0 cul u rdc c =( = 0 &(i>pu) #oia vct -tu i 0 r=) p ct lgcl eor re f ata 0btpeit1 cul u rdc rtr(enwih1*c +wih0*c) eunma(egt 1 egt 0) } 10-fold cross validation, note we are using the full data to train and evaluate the model. lbaybo) irr(ot cei.l3< gmY~X +X +X12 fml =bnma, rdtgm - l( 3 8 1_, aiy ioil cei.aa rdtdt) c.eut=c.l(rdtdt,cei.l3 cs1 1) vrsl vgmcei.aa rdtgm, ot, 0 c.eutdla vrsl$et # 008 008 #1 .70 .71 Search for optimal cut-off probability The following code does a grid search from pcut = 0.01 to pcut = 0.99 with the objective of minimizing overall cost in the...
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