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
[[alternative HTML version deleted]]
______________________________________________
[email protected] mailing list
https://stat.ethz.ch/mailman/listinfo/r-help
PLEASE do read the posting guide http://www.R-project.org/posting-guide.html
and provide commented, minimal, self-contained, reproducible code.
