Comments (3)
Hi,
thanks for letting me know. Looking forward to the update to pROC
. And pull requests are of course welcome!
I can't recall if it was a memory or speed issue with pROC
. I just ran the benchmarks again and indeed pROC
is faster now. I don't know why that is - maybe an update to pROC
or to R. It's not as fast as in your benchmarks, but I assume you are already using the updated version.
With OptimalCutpoints
and 1e5 observations I still get Error: cannot allocate vector of size 37.2 Gb
. ThresholdROC
finishes but is very slow (several minutes).
You're right that we should let ROCR
calculate sensitivity and specificity in the second benchmark. Below is what the results now look like for me. I'll push the new benchmarks to Github and also add a session info. I was planning to update the benchmarks eventually to use the bench
package instead of microbenchmark
because it also records the total memory allocation.
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I assume you are using pROC 1.14.0 from CRAN. It already has some improvements but the master branch on github is on par with ROCR now. You can try it out with devtools::install_github("xrobin/pROC")
.
I've made some minor changes in the way pROC is called, especially using the coords
function to find the best threshold. That one is very slow in 1.14.0. I'll update the data with the change in ROCR and send a pull request ASAP so you can see what's going on.
I see OptimalCutpoints
is trying to allocate a very large vector. Shouldn't be a problem with pROC then. I'd love to see a memory benchmark though, that would be very interesting!
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Continuing discussion in #20
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