Comments (6)
Any updates on installing the R package? Would love to explore using this package.
from xgboostlss.
it is because I am still working on getting it into a package, so there is no code yet pushed to the repo
from xgboostlss.
When is expected the availability of your package? Is it possible for you to upload your base codes for your work at this point? It will allow others to test your work too.
from xgboostlss.
The thing is that I am still working on getting the package ready, i.e., implementing additional distributions, unit tests and proper documentation. As such, there is no code yet on the repo. I am planning to have it ready by mid-year. I can only work on it during my spare time, so progress is very slow.
from xgboostlss.
Thank you so much for the updates. All the best.
from xgboostlss.
Kindly referring to #4 (comment).
from xgboostlss.
Related Issues (20)
- Support categorical features? HOT 1
- Support for XGBoost >= 1.6 HOT 2
- Loading Models - Losing Information HOT 4
- Cannot install package
- Cannot install package HOT 1
- Distribution error: Tensor of shape.. HOT 16
- Expectile Crossing and Predicted Distribution Recentering at Zero HOT 3
- Distribution loss_fn HOT 3
- Zero (and one?) adjusted Dirichlet? HOT 1
- Multi-task learning and ONNX support
- EvoTreesLSS?
- Support for censored probabilistic regression (survival analysis; AFT models) HOT 1
- Feature Request: Support Lambert W x F distributions
- Reducing `install_requires` to minimum (& expand `extras_require`) and looser version ranges HOT 3
- Regarding XGBoostLSS HOT 5
- Suggestion: spin-off the `distributions` module into a shared common dependency among all *lss modules HOT 1
- XGBoostLSSRegressor - Scikit Learn API HOT 4
- `skpro` integration HOT 1
- SHAP for categorical features HOT 2
- Could we use the new multi-output `xgboost` ?
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