[Question] Code for dspark projector adaptation?
Nobody has claimed this yet.
Assessment
- Difficulty
- 5/5
- Estimated time
- Over a week
- Newbie friendliness
- 20/100
- Issue type
- Feature
- Clarity
- Needs clarification
- Activity status
- Active
- Tech stack
- python
- Domain
- machine-learning
Research direction
The issue requests code or a reference branch for adapting DARTree to the dspark projector, but names no files, tests, or entry points. First determine the intended dspark integration scope and relevant project entry points; done would require an agreed implementation or reference branch, which the issue does not yet define.
Written by the indexing model from the issue text.
Description
Thanks for the great work and for open-sourcing the code :)
Would you be able to share the code / a reference branch for adapting DARTree's algorithm to the dspark projector?
- Dominant language
- Python
- Stars
- 11
- Forks
- 2
- PR merge metrics
- No merged PRs in 30d
Getting set up
This project ships no dev container, Dockerfile or contributing guide, so setting up is up to you: start from its README, and see our first-contribution guide for the general steps.
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.
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