Open-EO / Open-EO/openeo-python-client
Improve `fit_class_random_forest` and `fit_regr_random_forest` support
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api compliancy
usability
- Dominant language
- Python
- Stars
- 217
- Forks
- 56
- Avg merge
- 1d 22h
- Merged PRs (30d)
- 2
Description
A couple of issues with current (experimental) implementation of fit_class_random_forest and fit_regr_random_forest
- Add
fit_regr_random_forest - python client defines default
max_variables=null, while that's not the case in current process specs, see https://github.com/Open-EO/openeo-processes/issues/365 - methods
fit_class_random_forestandfit_regr_random_forestare defined on (raster) DataCube object, while it should be on vector cube. Underlying problem is thataggregate_spatialreturns a (raster) DataCube instead of VectorCube
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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 locating the implementations of fit_class_random_forest, fit_regr_random_forest, and aggregate_spatial in the Python client. Check the max_variables default against the referenced process specification and trace the returned cube type. Done means the defaults and method placement match the intended VectorCube API.
Written by the indexing model from the issue text.
Assessment
- Tech stack
- python
- Domain
- api, data, machine-learning
- Issue type
- Feature
- Difficulty
- 4/5
- Estimated time
- 3-5 days
- Activity status
- Stale
- Clarity
- Mostly clear
- Newbie friendliness
- 25/100