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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?

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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 this 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.

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    $\begingroup$ 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
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    $\begingroup$ @RobertdeGraaf Yes. It is a good paper. $\endgroup$ – SmallChess Mar 23 '17 at 5:53
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Yes, there is now a port to R, which is available here.

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.

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

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