tslearn-team / tslearn-team/tslearn
Implement metric learning for time series
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new feature
- Dominant language
- Python
- Stars
- 3.2k
- Forks
- 384
- Avg merge
- 3d 12h
- Merged PRs (30d)
- 11
Description
It would make sense to have metric learning algos dedicated to time series in tslearn.
A good start could be Garreau et al, 2014, but maybe other methods could make more sense.
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
No implementation file, test, or entry point is named. Start by reading the linked Garreau et al. 2014 paper and reviewing tslearn's existing algorithm structure; completion would require choosing a time-series metric-learning method and defining its implementation scope and validation.
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