library(MASS)
data(Pima.tr)
data(Pima.te)
?Pima.tr

#glm(type~age,data=Pima.tr)
#glm(type~age+ped+bp,data=Pima.tr)

glm1<-glm(type~npreg+glu+skin+bmi+age+ped+bp,data=Pima.tr, family="binomial")
pp1<-predict(glm1, data = Pima.tr, type = "response")

pred_tr=NULL
pred_tr[pp1<0.5]<-1
pred_tr[pp1>=0.5]<-2

confusion<-cbind(pred_tr,Pima.tr$type)

sum(confusion[,1]==2&confusion[,2]==2)
sum(confusion[,1]==1&confusion[,2]==1)
sum(confusion[,1]==1&confusion[,2]==2)
sum(confusion[,1]==2&confusion[,2]==1)

glm2<-glm(glm1,data=Pima.te,family="binomial")
pp2 <- predict(glm2, data = Pima.te, type = "response")

pred_test=NULL
pred_test[pp2<0.5]<-1
pred_test[pp2>=0.5]<-2

confusion2<-cbind(pred_test,Pima.te$type)

sum(confusion2[,1]==2&confusion2[,2]==2)
sum(confusion2[,1]==1&confusion2[,2]==1)
sum(confusion2[,1]==1&confusion2[,2]==2)
sum(confusion2[,1]==2&confusion2[,2]==1)