scikit-learn/scikit-learn

Consensus Index for Clustering Model Selection

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#11,778 opened on Aug 7, 2018

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Documentationhelp wantedmodule:cluster

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

Tech stack
python
Domain
documentationmachine learning
Issue type
documentation
DifficultyEstimated implementation difficulty for a new contributor, from 1 for very small changes to 5 for expert-level work.
2
Estimated timeA rough time range for an experienced contributor to investigate, implement, test, and prepare a pull request.
1-3 hours
Activity statusHow available the issue appears right now: fresh, active, stale, blocked, or waiting on maintainer input.
stale
ClarityHow clearly the issue explains the expected change, acceptance criteria, and next step.
clear
Prerequisites
basic understanding of clustering metrics
Newbie friendlinessA 1-100 score estimating how approachable this issue is for first-time contributors.
70
Research direction
Look at the scikit learn documentation for clustering metrics that mention 'Consensus Index'. Search for any existing write up or example workflow in the repository. Check the linked PRs or original author comments. Consider creating a new example notebook or adding a note in the documentation. If no prior work exists, outline a simple workflow using metrics like adjusted Rand index for model selection.