scikit-learn / scikit-learn/scikit-learn
Consensus Index for Clustering Model Selection
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Description
The sentence:
XXX can also be useful in a purely unsupervised setting as a
building block for a Consensus Index that can be used for clustering
model selection (TODO).
is in the description of every clustering metric that requires a ground truth label. Is there a write-up somewhere of an example workflow to build such a Consensus Index using these metrics? I searched through old issues and the original PRs creating this documentation and I can't see anything that looks like that. Though to be fair, I'm a big dummy, so I could just be missing it. If there isn't, is this TODO still really a TODO and is there an existing issue for it that I'm also too dumb to find? Thanks!
❤️
cc @ogrisel since you seem to be the og implementor and the original author of these docs.
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
Review the clustering metric descriptions, the old issues, and the original PRs mentioned in the report. Determine whether the Consensus Index TODO still represents missing documentation and identify a concrete example workflow to document. Done means the existing reference is either replaced with a useful write-up or the outdated TODO is removed, with the decision explained.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- documentation, machine-learning
- Issue type
- Documentation
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Active
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100