tslearn-team / tslearn-team/tslearn
Difference in results between tslearn and DBA.py implementation
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Description
I've been trying to use the average DBA function provided by tslearn to compute the average of a set of time series. However, I've noticed that the results obtained with tslearn's implementation and with the original DBA.py module by Francois Petitjean (https://github.com/fpetitjean/DBA/blob/master/DBA.py) seem to differ. I've attached graphs that illustrate the discrepancies. I've used the exact same data for both implementations.
I'm unsure whether this is due to a bug in the tslearn code or if I might have missed some modification that's required for the tslearn implementation. Could someone help me investigate this issue, please?
Thank you.
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 comparing tslearn's average DBA behavior with the original DBA.py implementation linked in the issue, using the exact same time-series data described by the reporter. Inspect the attached graph and determine whether the discrepancy is an implementation bug or a required usage difference; done means documenting the cause and, if applicable, identifying the needed correction.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- machine-learning
- Issue type
- Bug
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Needs clarification
- Newbie friendliness
- 25/100