Comments (3)
Do we really want this? Do we then get one extra commit message per commit?
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Similar as we do it in mlr currently: Build it (to check if everything is ok) but don't deploy. Update changed docs directly in the PR and merge silently.
I recently had a long discussion with Bernd and Jakob before about the best approach. Currently, there is no option that has no drawback.
The problem is that pkgdown::build_site()
updates all .png files and the seed is not respected. This then sets the files to "changed" in git and we get a new commit deployed. Once they have resolved this issue we can again auto-deploy.
Big advantage of master/docs to gh-pages: PR preview of the changed site which is a very important feature.
As long as the site is minimal, we can serve through the gh-pages branch.
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To have the pkgdown site as a subdomain mlr3.mlr-org.com, we need to have it in master/docs
because the deployment to gh-pages
deletes the CNAME
file on every push because its doing an orphan = T
push.
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Related Issues (20)
- Retrieve data from learner HOT 6
- Release mlr3 0.20.1
- Licensing issue due to mlr3 dependnency RhpcBLASctl HOT 3
- Release mlr3 0.20.2
- Unexpected Feature Inclusion in mlr3 Task Definition HOT 4
- Allow Multiple Ratios in partition() for Creating Training, Testing, and Validation Sets HOT 2
- learner predict HOT 1
- `MeasurerElapsedTime` uses "mean" for aggregation the total time, while "sum" would be more appropriate HOT 1
- Accessing `col_info` is a bottleneck
- Set environment variables to disable parallelization
- remove some unneeded marshal tests
- Add FAQ on workaround to use model trained with old mlr3 version
- Add `set_internal_tuning()` helper method for configuring internal hyperparameter optimization
- Feature Request: Allow no required predict sets for a `Measure` HOT 1
- Issues with as.data.table(mlr_learners) Function HOT 2
- Measures: the whole NA handling seems overly complicated
- Should Learners that implement '$loglik()' have a "loglik" property? HOT 1
- debug learners should implement importance, selected_features, oob_error and loglik
- Learner / measure: OOB error seems too restrictive, cannot take mlr3 measure
- BenchmarkResult object doesn't save predictions anymore
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