scikit-learn / scikit-learn/scikit-learn
Add target for plot_roc_curve
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Hard
module:metrics
New Feature
- Dominant language
- Python
- Stars
- 67.3k
- Forks
- 27.4k
- Avg merge
- 1d 15h
- Merged PRs (30d)
- 58
Description
Similar to how in plot partial dependence we have:
target : int, optional (default=None)
- In a multiclass setting, specifies the class for which the PDPs
should be computed. Note that for binary classification, the
positive class (index 1) is always used.
- In a multioutput setting, specifies the task for which the PDPs
should be computed
Ignored in binary classification or classical regression settings.
Contributor guide
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 locating the plot_roc_curve implementation and the existing plot partial dependence target handling. Define the target behavior for multiclass and multioutput settings, then verify that the resulting ROC plot uses the selected class or task and that the documented behavior is covered by tests.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- data-visualization, machine-learning
- Issue type
- Feature
- Difficulty
- 3/5
- Estimated time
- 1-2 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100