scikit-learn / scikit-learn/scikit-learn
types in dataset bunches are inconsistent
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module:datasets
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- Dominant language
- Python
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Description
I just saw that iris.feature_names is a list but iris.target_names is an array. That is odd. Not sure how it is for the other datasets.
This is pretty minor but some consistency would be nice.
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 comparing the types returned by iris.feature_names and iris.target_names, then inspect the corresponding attributes across the other datasets mentioned in the issue. Define a consistent type for these dataset name collections and verify that all affected dataset loaders follow it.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100