Comments (1)
- Thanks for the heads up @be-marc 👍.
- I checked your repo. I assume you plan to submit version 0.6.0?
- We will adapt accordingly. Test it vs. your dev version from https://github.com/mlr-org/mlr3tuning and then also publish a minor release to CRAN with the fix.
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Related Issues (20)
- Unit test for the extraction of predictions fails for non-glmnet learner HOT 1
- Support for Categorical D in PLIV HOT 1
- Support for ensemble multiple learners for ml_g and ml_m HOT 2
- Make DoubleML available for R (≥ 4.0.2) HOT 1
- Failing builds on github actions with development version of mlr3 HOT 2
- [Bug]: the result of Lasso learner is different from others
- [Bug]: Unable to perform ensemble learners HOT 2
- Depreciation warning when applying pkgdown
- [Bug]: Tuning with default `tune_settings` fails
- [Bug]: Tuning with default `tune_settings` fails
- Inconsistent initilization of `task_type` between PLIV and other models (PLR, IRM, IIVM) HOT 3
- [Bug]: Tuning fails with non-meaningful error message when `tune_settings$measure` real subset of the nuisance parts HOT 3
- [Unit Test Extension]: Implement "default setting unit tests"
- [CRAN]: Issue with html check HOT 1
- [API Documentation]: Include documentation for `store_models` option in `DoubleML$fit()`
- [Feature Request]: In IRM Model , allow for different learners for `g0` and `g1`
- [Feature Request]: Classification Learner for `ml_l` HOT 4
- Update workflows for deploy of docu
- [Bug]: `store_predictions=TRUE` in `fit()` does not save results with more than one treatment
- [Feature Request]: Observation weights HOT 1
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