Review a random sample of highways
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- Dominant language
- Jupyter Notebook
- Stars
- 19
- Forks
- 6
- PR merge metrics
- No merged PRs in 30d
Description
Ref: https://github.com/mapbox/gabbar/issues/69 and https://github.com/mapbox/gabbar/issues/80
I prepared a random sample of highway features touched to manually 👀 for identifying good and harmful highways. We then use this knowledge to make the highway classifier better.
With @amishas157's help, I created a To-Fix task with `9,533` randomly selected highways. I used the `Not an error` button for good highways and `Fixed` button for harmful highway.
- To-Fix task: https://osmlab.github.io/to-fix/#/task/labellinghighwaysforgabbar
To start with I reviewed `100` highways and did not find any harmful.
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cc: @anandthakker @batpad @geohacker
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
Open the To-Fix task at https://osmlab.github.io/to-fix/#/task/labellinghighwaysforgabbar and review the randomly selected highway features using the Not an error or Fixed actions described in the issue. Start with the task instructions and referenced issues #69 and #80; done means labeling the assigned sample so the results can inform the highway classifier.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- jupyter-notebook, scikit-learn
- Domain
- data, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- Over a week
- Activity status
- Stale
- Clarity
- Clearly specified
- Newbie friendliness
- 35/100