dssg / dssg/triage

Experiment should merge redundant feature group subsets

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trivial
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Jupyter Notebook
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201
Forks
62
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No merged PRs in 30d

Description

If the user creates a bunch of feature group subsets, there can be some redundancy. We should do some mixture of:

- blowing up in the experiment validator if they do configuration that makes no sense (like mixing all-combinations with anything else)
- merging redundant subsets if they are arrived at through sane config (e.g. leave-one-in and leave-one-out overlap)

Contributor guide

Open the contributing guide

Research direction

Start by locating the experiment validator and the code that constructs feature-group subsets. Determine which configurations are invalid, including mixing all-combinations with other modes, and how leave-one-in and leave-one-out overlap. Done means invalid configurations fail validation and valid redundant subsets are merged, with tests covering both cases.

Written by the indexing model from the issue text.

Assessment

Tech stack
python
Domain
machine-learning
Issue type
Feature
Difficulty
5/5
Estimated time
Over a week
Activity status
Stale
Clarity
Needs clarification
Newbie friendliness
25/100

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