JuliaAI / JuliaAI/MLJTutorial.jl
Make model in tute 02 reproducible
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- Dominant language
- Julia
- Stars
- 28
- Forks
- 2
- Avg merge
- 4h 17m
- Merged PRs (30d)
- 14
Description
@roland-KA has notices that misclassification_rate is occassionially zero, which might confuse some users. Perhaps consider a reproducible model (this one uses Flux dropout which cannot be passed an RNG at time of writing).
Contributor guide
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First steps
- Read the whole issue, then the project's contributing guide.
- Comment on the issue to say you are picking it up — it saves two people doing the same work.
- Fork the repository and make your change on a branch.
- Open a pull request that references the issue number.
Research direction
Open tute 02 and run the model repeatedly to reproduce the occasional zero misclassification_rate. Trace how the Flux dropout model is created and how randomness is handled; done means the tutorial uses a reproducible model whose result does not vary unexpectedly between runs.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- julia
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 42/100