tslearn-team / tslearn-team/tslearn
Would you like to implement unsupervised Salient Subsequence Learning (USSL) in tslearn?
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- Dominant language
- Python
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Description
Qin published an article titled "Salent subsequence learning for time series clustering" in IEEE Transactions on pattern analysis and machine intelligence in 2018.This paper proposes an unsupervised Salient Subsequence Learning (USSL) model that discovers shapelets without the effort of labeling.This method has obvious advantages compared with KDBA, KSC and u-shapelet methods, but they did not publish the code in GitHub as described in the article. Would you like to implement it in tslearn?
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
The issue names no target files, tests, or entry point. Start by reading Qin's 2018 paper on Salient Subsequence Learning and determine how its USSL model would fit into tslearn's existing time-series clustering APIs. Done would require an agreed implementation scope and validation approach, neither of which is specified here.
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
- 20/100