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@StatMixedML StatMixedML released this 23 May 15:56
· 141 commits to master since this release

Enhanced Distributional Modeling with PyTorch

  • LightGBMLSS now fully relies on PyTorch distributions for distributional modeling.
  • The integration with PyTorch distributions provides a more comprehensive and flexible framework for probabilistic modeling and uncertainty estimation.
  • Users can leverage the rich set of distributional families and associated functions offered by PyTorch, allowing for a wider range of modeling options.

Automatic Differentiation

  • LightGBMLSS now fully leverages PyTorch's automatic differentiation capabilities.
  • Automatic differentiation enables efficient and accurate computation of gradients and hessians, resulting in enhanced model performance and flexibility.
  • Users can take advantage of automatic differentiation to easily incorporate custom loss functions into their LightGBMLSS workflows.
  • This enhancement allows for faster experimentation and easier customization.

Hyper-Parameter Optimization

  • LightGBMLSS now enables the optimization of all LightGBM hyper-parameters for enhanced modeling flexibility and performance.

What's Changed:

  • The syntax of LightGBMLSS has been updated in this release. We have made improvements to certain aspects of the syntax to provide better clarity and consistency.
  • To familiarize yourself with the updated syntax, we kindly refer you to the example sections. The examples will demonstrate the revised syntax and help you adapt your code accordingly.

Bug Fixes

  • Several minor fixes and improvements have been implemented in this release.