Depends on the internal storage of the random forest model. You might need to
create a custom serializer:
https://github.com/JuliaLang/JLD.jl/blob/master/doc/jld.md#custom-serialization
--Tim
On Thursday, January 21, 2016 12:57:08 PM Ian Watson wrote:
> Using DecisionTree to build a random forest model. Small, 200 items, 664
> predictors for each item, input file size under 1 MB
>
> I can build a random forest model with 1000 trees in about 8 seconds -
> great.
>
> @time model=build_forest(yvalues[:,1],features,2,1000,0.5)
>
> Then I tried to save that model for subsequent scoring by writing it to a
> JLD file.
>
> Writing to an NFS mounted disk took multiple minutes, while writing a 194MB
> (!!) file.
>
> If I write that to /dev/shm, it still takes 51 seconds (and still 194MB)
>
> @time save("/dev/shm/foo.jld","model",model)
> 51.406531 seconds (12.01 M allocations: 465.667 MB, 0.38% gc time)
>
> When I do something comparable in R with the same dataset, build the model
> and then use save() to save the model and the features, the whole process
> takes about 14 seconds, and is 2.8MB on disk. The save() part of the
> processing is very fast.
>
> whos() shows
>
> model 6884 KB DecisionTree.Ensemble
>
> so if this is a good estimate of memory, I don't think the problem is with
> the DecisionTree object.
>
> Am I doing something wrong, or is JLD doing something horrible?
>
> Saw this. https://github.com/JuliaLang/julia/issues/7893, so perhaps
> problems still persist?
