# Parallel Random Forest

**URL:** <https://discourse.julialang.org/t/parallel-random-forest/2401>\
**Category:** General Usage\
**Tags:** question\
**Created:** [March 2, 2017, 5:32am UTC](https://discourse.julialang.org/t/parallel-random-forest/2401 "2017-03-02T05:32:44Z")\
**Posts on this page:** 4\
**Page:** 2

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**Author:** ![microgold](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/microgold/32/5404_2.png) [@microgold](https://discourse.julialang.org/u/microgold)\
**Post date:** [November 11, 2018, 10:51pm UTC](https://discourse.julialang.org/t/parallel-random-forest/2401/21 "2018-11-11T22:51:19Z")

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I also had some trouble compiling XGBoost on the PC but finally got it working with the latest version of Julia 1.0.1. Below is a link explaining how to use XGBoost with Julia on a PC. It would vary only slightly with the Linux version.

> **[Using Julia Random Forests and XGBoost to Diagnose Breast Cancer](https://www.linkedin.com/pulse/using-julia-random-forests-xgboost-diagnose-breast-cancer-mike-gold/)**
>
> Introduction In our last article, we used Julia and Flux to classify handwritten images of digits. In this article we will experiment more with Random Forests to classify benign and malignant cancers from a data set of cell features using real world...

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**Author:** ![Ajaychat3](https://avatars.discourse-cdn.com/v4/letter/a/ecd19e/32.png) [@Ajaychat3](https://discourse.julialang.org/u/Ajaychat3)\
**Post date:** [November 12, 2018, 9:25am UTC](https://discourse.julialang.org/t/parallel-random-forest/2401/22 "2018-11-12T09:25:53Z")

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Thanks @microgold. I am able to run it now.

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**Author:** ![pharten](https://avatars.discourse-cdn.com/v4/letter/p/c6cbf5/32.png) [@pharten](https://discourse.julialang.org/u/pharten)\
**Post date:** [April 30, 2019, 12:30pm UTC](https://discourse.julialang.org/t/parallel-random-forest/2401/23 "2019-04-30T12:30:30Z")

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Bernhard,

I am considering using Parallel Random Forest in Julia on Amazon Web Services for research purposes. Through the use of its macros, can does Julia send out tasks to multiple nodes with different number of cores on each node, but sidestep Python altogether?

Thanks,

Paul H.

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**Author:** ![mantzaris](https://sea2.discourse-cdn.com/julialang/user_avatar/discourse.julialang.org/mantzaris/32/3852_2.png) [@mantzaris](https://discourse.julialang.org/u/mantzaris)\
**Post date:** [May 2, 2019, 10:31pm UTC](https://discourse.julialang.org/t/parallel-random-forest/2401/24 "2019-05-02T22:31:58Z")

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Random Forests as an ensemble method can be easily parallelized in comparison to non-ensemble methods, as a simple aggregation (summation as it does rely on the ‘bagging/bootstrap aggregation’). Each prediction the randomForests\_predict model provides is due to a summation of the bagged samples produced, so aggregating based upon nested aggregates should be fine if the implementation is in line with the theory. Eg. doing this with a map-reduce where you run the full data or some sample of the rows with replacement. So on the ‘outside’ should be possible

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