# RandomForest with out of bag prediction

**URL:** <https://discourse.julialang.org/t/randomforest-with-out-of-bag-prediction/49377>\
**Category:** Machine Learning\
**Created:** [October 31, 2020, 5:50pm UTC](https://discourse.julialang.org/t/randomforest-with-out-of-bag-prediction/49377 "2020-10-31T17:50:09Z")\
**Posts on this page:** 1\
**Page:** 1

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**Author:** ![lubo](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/lubo/32/18895_2.png) [@lubo](https://discourse.julialang.org/u/lubo)\
**Post date:** [October 31, 2020, 5:50pm UTC](https://discourse.julialang.org/t/randomforest-with-out-of-bag-prediction/49377/1 "2020-10-31T17:50:09Z")

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Hi,

please, is there any implementation of RandomForest with Out of bag predictions?  
Seems to the reference RF package DecisionTree.jl has still this only as TODO (long time). Another package with OOB RandomForests.jl seems to be not actively developed.  
Thanks a lof for any direction - as I know I can use pycall a call python ScikitLearn, but this is very slow implementation.

Lubo