I found that xgboost generates an exception under RFECV when the number of features remaining falls below 3. I fixed this for myself by adding a 'stop_at' parameter (default=1) that stops the process in RFE when the remaining features falls below this number. I think it might be a useful feature more broadly than simply as a hacked work-around so I offer it as a pull request.
George Fisher geo...@georgefisher.com +1 917-514-8204 https://github.com/grfiv Ubuntu 17.04 Desktop Python 3.5.3 IPython 6.0.0 sklearn 0.18.1 (xgboost 0.6)
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