rust-ml / rust-ml/linfa

Sparse PCA

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#143 3 comments 0 reactions 0 assignees View on GitHub

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enhancement
Dominant language
Rust
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Avg merge
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Merged PRs (30d)
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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 sparse flag?
  • 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.

Written by the indexing model from the issue text.

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

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