Hello All, 
I have used logistic regression glm in R and I am evaluating two models both learned with glm but with different predictors. model1 <- glm (Y ~ x4+ x5+ x6+ x7, data = dat, family = binomial(link=logit))model2 <- glm (Y~ x1 + x2 +x3 , data = dat, family = binomial(link=logit)) 
and I would like to compare these two models based on the prediction that I get from each model:
pred1 = predict(model1, test.data, type = "response")pred2 = predict(model2, test.data, type = "response")
I have used ROCR package to compare them:pr1 = prediction(pred1,test.y)pf1 = performance(pr1, measure = "prec", x.measure = "rec")  plot(pf1) which cutoff this plot is based on?
pr2 = prediction(pred2,test.y)pf2 = performance(pr2, measure = "prec", x.measure = "rec")pf2_roc  = performance(pr2,measure="err")plot(pf2)
First of all, I would like to use cutoff = 0.5 and plot the ROC, precision-recall curves based on that cutoff value. In other words, how to define a cut off value in performance function?For example, in pf2_roc  = performance(pr2,measure="err"), when I do plot(pf2_roc), it plots for every single cutoff point. I only want to have one cut off point, is there any way to do that?Second, I would like to see the performance of the two models based on the above measures on the same plot so the comparison would be easier. In other words, how can I plot (pf1, pf2) and compare them together?plot(pf1, pf2) would give me an error as follows:Error in as.double(x) :   cannot coerce type 'S4' to vector of type 'double'
Could you please help me with that?
Thanks a lot,Andra



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