Sparse PCA
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enhancement
- Dominant language
- Rust
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Description
(Related to #22)
Hey,
I would like to start implement sparse PCA and I have a question and need for feedback, as my ML experience is minute.
- Should we implement a separate algorithm (like scikit-learn does) or just use a
sparseflag? - By reading the sparse PCA paper linked in the original issue, the R implementation by the author, and this Python implementation, I have arrived at this (hyper)parameter list:
n_components(P)l1_penalty(H)l2_penalties(H)max_n_iterations(P)tolerance(P)
- I am not sure which of these should be parameters (P) and hyperparameters (H), feel free to comment on that or anything I missed here.
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Research direction
Start with related issue #22, then read the linked scikit-learn, Stanford paper, R elasticnet implementation, and Python implementation. The issue needs a maintainer decision on the API, parameters, and implementation scope before completion can be defined.
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Assessment
- Tech stack
- rust
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 5/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 20/100