Input array feature smaller than 3
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- Dominant language
- Python
- Stars
- 188
- Forks
- 28
- PR merge metrics
- No merged PRs in 30d
Description
It seems like we cannot fit ndarray smaller than shape(-1,3).
e.g.
if we want to fit in some array of shape(-1,2):

And it will call a function in gen_meta_features, and do PCA, but the param is a fixed "3".

Also, is it better that "select_model" returns a list of models with its hyperparams. For now, I need to print out the best N selected models and new these models by my own. If the top models is "LODA (5, 100)", I can't simply do "clf = LODA(5,100)", instead, I need to do "LODA(n_bins=5, n_random_cuts=100)" or "LODA(0.1, 5, 100)"
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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 by reading the gen_meta_features and select_model entry points mentioned in the issue, then reproduce the shape(-1,2) case. Clarify whether the goal is only to remove the fixed dimensionality limit or also to change select_model's return value; done should include a defined behavior for both requests and coverage for the supported input shape.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 30/100