JuliaAI / JuliaAI/DecisionTree.jl
Input checking
Open
Nobody has claimed this yet.
- Dominant language
- Julia
- Stars
- 364
- Forks
- 100
- PR merge metrics
- No merged PRs in 30d
Description
This is scary:
tree = fit!(DecisionTreeRegressor(), [1.0 2; 3 4], [10, 24.0])
predict(tree, [])
> 17.0
apply_tree also accepts (and ignores) extra values in the feature_vector without complaining.
Contributor guide
No contributing guide indexed for this repository
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
Start by tracing the predict(tree, []) example and the apply_tree entry point to find where feature vectors are checked. Confirm the behavior for missing and extra values, then add input validation so both cases fail clearly and verify the behavior with the relevant existing tests.
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
- 30/100