mne-tools / mne-tools/mne-python
BUG..?: linear_regression_raw doesn't warn for rank deficiency
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- Python
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Description
Passing predictors that will lead to a rank deficient matrix to linear_regression_raw should throw an error or at least a big fat warning. Currently, it silently computes a stupid solution.
This is in my experience a very common scenario.
An extremely easy way may be checking the rank of the resulting predictor matrix.
(It would also be nice to estimate the degree of multicollinearity in the model.)
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 at the linear_regression_raw entry point and reproduce the issue with predictors that produce a rank-deficient matrix. Review the surrounding behavior and existing tests to determine whether the expected result should be an error or a prominent warning. Done means rank-deficient input no longer silently produces a solution, with coverage for the selected behavior.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 35/100