This is very easy to do just make sure to input your model name into it. *change

D<-with(

*Themodelnamrit#1inR(,1.249852-0.046024*BNucl-0.020809*USize-0.032588*Thick-

0.019955*NNucl-0.019872*Chrom-0.014199*UShap-0.010331*Epith-0.007912*Adhes)

(this is the updated model)$p <- with(*this is the updated model,exp(Predx1) / (1+exp(Predx1)))

*this is the updated model$PMClass <- withthis is the updated model,abs(p-Class))

for(i in 1:length(this is the updated model$PMClass)){

if(*this is the updated model$PMClass*<0.5)*

{

*this is the updated model$error* <- 0*

}else

{

*this is the updated model$error* <- 1*

}

}

*this is the updated model$ClassMp <- with(this is the updated model,Class-p)

*this is the updated model$er1 <- rep(0,length(*this is the updated model$ClassMp))

for(i in 1:length(*this is the updated model$ClassMp)){

if(*this is the updated model$ClassMp*<-0.9 && *this is the updated model$ClassMp**>0.1)*

{

*Updatemode$er1* <- 1*

}else

{

this is the updated model$er1* <- 0*

}

}

sum(*this is the updated model$ClassMp)

> sum(*this is the updated model$ClassMp)

[1] 443