1
$\begingroup$

One of the researchers, Marco Ribeiro, who developed this method of explaining how black box models make their decisions has developed a Python implementation of the algorithm available through Github, but has anyone developed a R package? If so, can you report on using it?

$\endgroup$
3
$\begingroup$

I think you're talking about the lime Python package. No, there is no R port for the package. The implementation for the localized model requires enhancements to the existing machine-learning code (explained in the paper), a new implementation for R would be very time consuming.

You may want to take a look at https://stackoverflow.com/questions/11716923/python-interface-for-r-programming-language for interfacing Python in R.

My suggestion is stick with Python. The package is only useful for highly complicated non-linear models, which Python offers better support than R.

| improve this answer | |
$\endgroup$
  • 1
    $\begingroup$ To clarify - when you say 'the paper' do you mean 'Why Should I Trust You?' by Ribeiro, Singh and Guestrin, date stamped 16 Feb 2016 in arXiv? $\endgroup$ – Robert de Graaf Mar 23 '17 at 5:52
  • 1
    $\begingroup$ @RobertdeGraaf Yes. It is a good paper. $\endgroup$ – HelloWorld Mar 23 '17 at 5:53
4
$\begingroup$

Yes, there is now a port to R, which is available here: https://github.com/thomasp85/lime

It purports to provide LIME explanations for any classifier that implements a predict() method accepting a type = 'prob' argument. I have not yet tested it myself.

| improve this answer | |
$\endgroup$
  • $\begingroup$ Great news! (note: comment made before trying it out ;-)) $\endgroup$ – Robert de Graaf May 17 '17 at 0:01

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.