On Apr 6, 2011, at 2:27 PM, Christian Meesters wrote:
Hi,
My questions concerns the ROCR package and I hope somebody here on
the list can help - or point me to some better place.
When evaluating a model's performane, like this:
pred1 <- predict(model, ..., type="response")
pred2 <- prediction(pred1, binary_classifier_vector)
perf <- performance(pred, "sens", "spec")
(Where "prediction" and "performance" are ROCR-functions.)
How can I then retrieve the cutoff value for the sensitivity/
specificity tradeoff with regard to the data in the model (e.g.
model = glm(binary_classifier_vector ~ data, family="binomial",
data=some_dataset)? Perhaps I missed something in the manual?
Or perhaps in your learning phase regarding decision theory perhaps?
You have not indicated that you understand the need to assign a cost
to errors of either type before you can talk about a preferred cutoff
value.
Or do I need an entirely different approach for this? Or is there an
alternative solution?
Thanks,
Christian
--
David Winsemius, MD
West Hartford, CT
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