Step idea: `step_pca_cliques()`
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feature
- Dominant language
- R
- Stars
- 146
- Forks
- 23
- PR merge metrics
- No merged PRs in 30d
Description
General algorithm:
- run correlation on whole data set
- find cliques or near cliques
- apply PCA on each clique
ref: https://www.newsletter.quantreo.com/p/the-pca-trick-i-use-all-the-time
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 with the proposed step_pca_cliques() entry point and read the linked PCA trick reference. Work through the stated sequence—correlation on the whole data set, finding cliques or near cliques, and applying PCA to each clique—and establish the expected behavior before implementation.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- r
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100