JuliaAI / JuliaAI/DecisionTree.jl
Problems saving random forest model
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- Dominant language
- Julia
- Stars
- 364
- Forks
- 100
- PR merge metrics
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Description
Hi all,
I'm having a strange problem when saving a random forest model. When using the JLD module to save the model created by the DecisionTree module, it usually takes a huge amount of space on disk. For instance, a model that had a size of 155 Mb as a variable in julia, would take more than 2 Gb to save in disk and an eternity to save the model!
I solved this problem by using the serialize and deserialize commands. After this, I was able to save the models. However, the drawback of this method is that maybe it won't be possible to read the models in
other Julia versions. I didn't know if this is an issue from the DecisionTree module or the JLD module but would like to know if you have another workaround.
Cheers,
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Research direction
The report mentions JLD, the DecisionTree random forest model, and Julia's serialize/deserialize commands, but names no files, tests, or entry points. Start by reproducing the size and save-time difference with the reported model, then compare JLD and serialization behavior across Julia versions. Done should identify whether JLD or DecisionTree causes the expansion and document a reliable workaround.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100