Logistic Regression, Prediction and ROC

Et fl oe x3 adx1rcvl n 12oo httpsblackboar

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Unformatted text preview: oded {0, 1 } )”. The second argument is the vector with predicted probability. lbay"eiiain) irr(vrfcto" rcpo(rdtts$ = "" po.l1otape o.ltcei.etY = 1, rbgm.usml) To get the area under the ROC curve: rcpo(rdtts$ = "" po.l1otape$o.o o.ltcei.etY = 1, rbgm.usml)rcvl https://blackboar d.uc.edu/bbcswebdav/pid- 9566224- dt- content- r id- 55868231_2/cour ses/14SS_BANA7046002/notes%284%29.html 7/15 2/17/2014 Log istic Reg r ession, Pr ediction and ROC # # Mdl Ae oe ra pvlebnr.ra .au iomae # 1Mdl 1077 107-6 # oe .58 .7e0 N A We can also compare the glm0 and glm1 on the same graph: po.l0otape< peitcei.l0 cei.et rbgm.usml - rdc(rdtgm, rdtts, tp ="epne) ye rsos" rcpo( =cei.etY= "" pe = o.ltx rdtts$ = 1, rd cidpo.l0otape po.l1otape, bn(rbgm.usml, rbgm.usml) lgn =TU,lgtx =c"ulMdl,"_,X8 eed RE e.et (Fl oe" X3 _, adX1_")rcvl n _12)$o.o https://blackboar d.uc.edu/bbcswebdav/pid- 9566224- dt- content- r id- 55868231_2/cour ses/14SS_BANA7046002/notes%284%29.html 8/15 2/17/2014 Log...
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