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@StatMixedML StatMixedML released this 26 May 14:34
· 384 commits to master since this release
v0.2.1
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Learn about vigilant mode.

We are excited to announce the release of xgboostlss v0.2.1! This release brings several new features, stability improvements, and bug fixes. Here are the key highlights of this release:

New Features

  • Flexible Distribution Selection: We have introduced a new function that allows users to choose from a variety of candidate distributions for modeling. You can now select the most suitable distribution for your data, enabling more accurate and customized predictions.

  • Expectile Penalty: We have enhanced the expectiles functionality by introducing a penalty that discourages crossing of expectiles during training. This helps to improve the coherence of the expectile predictions, leading to more reliable models.

Stability Improvements

  • Parameter Initialization: We have made stability improvements in the parameter initialization process. This ensures that the model starts from a more robust and reliable state, reducing the chances of convergence issues and enhancing the overall performance.

  • Model Estimation: We have also improved the stability of the model estimation process. This results in more consistent and accurate estimation of model parameters, leading to better predictions and increased model reliability.

Bug Fixes

In addition to the new features and stability improvements, we have addressed various bugs reported by the community. These bug fixes enhance the overall reliability and usability of xgboostlss.

General

We appreciate the valuable feedback and contributions from our users, which have helped us in making xgboostlss even better. We encourage you to update to this latest version to take advantage of the new features and improvements.

Thank you for your continued support, and we look forward to your feedback.

Happy modeling!

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