Generalize target param computation framework
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- Dominant language
- Python
- Stars
- 124
- Forks
- 24
- Avg merge
- 19h 32m
- Merged PRs (30d)
- 60
Description
similar to the `angle` in the name, here we shouldn't hardcode `_v_` in the function name.
The learning rule could be applied to any parameter, we should use a name for it that just reflects the type of updating we are doing, regardless of which parameter it is applied to.
_Originally posted by @AlexanderFengler in https://github.com/lnccbrown/HSSM/pull/824#discussion_r2484104499_
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 by locating the target parameter computation and the function names that currently hardcode `_v_`, then read the related discussion in pull request 824. Compare this naming with the existing `angle` naming. Done means the learning rule can be applied to any parameter without parameter-specific naming assumptions.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Refactor
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 35/100