autogluon / autogluon/tabarena

[Suggestion] some potentially other useful subsets for BeyondArena

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#516 5 comments 0 reactions 0 assignees View on GitHub
Dominant language
Python
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Forks
69
Avg merge
1d 4h
Merged PRs (30d)
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Description

These are some potentially useful subsets for the filter, as these data sets are common:

- Data sets with joint groups between train and test. There's already a subset with disjoint groups, so it would be easy to implement the opposite.
- Noisy data
- Sparse data

Contributor guide

Open the contributing guide

Research direction

Start by tracing how the existing disjoint-groups subset is defined and exposed in the dataset-filtering code. Confirm the intended definitions for joint train/test groups, noisy data, and sparse data with the issue discussion; done means the requested subsets are available through the filter and covered by the project's existing checks.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Feature
Difficulty
3/5
Estimated time
1-2 days
Activity status
Active
Clarity
Mostly clear
Newbie friendliness
58/100

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