Changes in version 1.1 (2024-03-18)                   

New features

  - hyperparameter tuning (experimental)
  - burnin parameter
  - multivariate probit model
  - X and Y support (alternative interface)
  - negative binomial distribution

Minor changes

  - Improved vignette
  - Improved README

Bug fixes

  - dropout is turned off after training (into evaluation mode)
  - predict type was changed
  - small bug in the activation functions
  - extended support for mps devices

                 Changes in version 1.0.2 (2023-10-06)                  

New features

  - conditional Effects (approximate linear effects)
  - uncertainties via bootstrapping (can be forwarded to all functions)
  - summary() can return standard errors and p-values for xAI metrics
  - improved documentation / several new vignettes
  - baseline loss
  - loss = inf/na is not captured, training is aborted and user will be
    warned
  - mps (M1/M2 gpu) device is now supported

Bug fixes

  - early stopping (ignored validation loss)
  - weights are only saved for best and last epoch
  - gaussian likelihood works now properly
  - reguarlization loss is not visualized
  - reduce lr on plateau works now with validation loss

                 Changes in version 1.0.1 (2023-03-13)                  

New features

  - predict function can now return directly the class
  - custom loss and parameter can now also be optimized
  - summary function (importances) does now support loss = binomial

Minor changes

  - print of summary is now more clear

Bug fixes

  - in ALE function providing new data did not work properly
  - Performance improvements with new dataloader
  - ALE/PDP work now correctly for softmax
  - PDP ICE return now correct curves
  - Early stopping works now
  - lr reducer on plateau didn't reduce lr
  - Predictions are now made on cuda of the model is stored on cuda